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details.json
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{
"Binary classification": {
"Dataset": {
"Bananas": "Bananas dataset.\n\nAn artificial dataset where instances belongs to several clusters with a banana shape.\nThere are two attributes that correspond to the x and y axis, respectively.\n\n Name Bananas \n Task Binary classification \n Samples 5,300 \nFeatures 2 \n Sparse False \n Path /Users/mastelini/miniconda3/envs/river-benchmark/lib/python3.10/site-packages/river/datasets/banana.zip",
"Elec2": "Electricity prices in New South Wales.\n\nThis is a binary classification task, where the goal is to predict if the price of electricity\nwill go up or down.\n\nThis data was collected from the Australian New South Wales Electricity Market. In this market,\nprices are not fixed and are affected by demand and supply of the market. They are set every\nfive minutes. Electricity transfers to/from the neighboring state of Victoria were done to\nalleviate fluctuations.\n\n Name Elec2 \n Task Binary classification \n Samples 45,312 \n Features 8 \n Sparse False \n Path /Users/mastelini/river_data/Elec2/electricity.csv \n URL https://maxhalford.github.io/files/datasets/electricity.zip\n Size 2.95 MB \nDownloaded True ",
"Phishing": "Phishing websites.\n\nThis dataset contains features from web pages that are classified as phishing or not.\n\n Name Phishing \n Task Binary classification \n Samples 1,250 \nFeatures 9 \n Sparse False \n Path /Users/mastelini/miniconda3/envs/river-benchmark/lib/python3.10/site-packages/river/datasets/phishing.csv.gz",
"SMTP": "SMTP dataset from the KDD 1999 cup.\n\nThe goal is to predict whether or not an SMTP connection is anomalous or not. The dataset only\ncontains 2,211 (0.4%) positive labels.\n\n Name SMTP \n Task Binary classification \n Samples 95,156 \n Features 3 \n Sparse False \n Path /Users/mastelini/river_data/SMTP/smtp.csv \n URL https://maxhalford.github.io/files/datasets/smtp.zip\n Size 5.23 MB \nDownloaded True "
},
"Model": {
"Logistic regression": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n LogisticRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.005\n )\n )\n loss=Log (\n weight_pos=1.\n weight_neg=1.\n )\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n)",
"Aggregated Mondrian Forest": "[]",
"ALMA": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n ALMAClassifier (\n p=2\n alpha=0.9\n B=1.111111\n C=1.414214\n )\n)",
"sklearn SGDClassifier": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n SKL2RiverClassifier (\n estimator=SGDClassifier(eta0=0.005, learning_rate='constant', loss='log_loss',\n penalty=None)\n classes=[False, True]\n )\n)",
"Vowpal Wabbit logistic regression": "VW2RiverClassifier ()",
"Naive Bayes": "GaussianNB ()",
"Hoeffding Tree": "HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n)",
"Hoeffding Adaptive Tree": "HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=True\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=42\n)",
"Adaptive Random Forest": "[]",
"Streaming Random Patches": "SRPClassifier (\n model=HoeffdingTreeClassifier (\n grace_period=50\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=0.01\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n )\n n_models=10\n subspace_size=0.6\n training_method=\"patches\"\n lam=6\n drift_detector=ADWIN (\n delta=1e-05\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n warning_detector=ADWIN (\n delta=0.0001\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n disable_detector=\"off\"\n disable_weighted_vote=False\n seed=None\n metric=Accuracy (\n cm=ConfusionMatrix (\n classes=[]\n )\n )\n)",
"k-Nearest Neighbors": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n KNNClassifier (\n n_neighbors=5\n engine=SWINN (\n graph_k=20\n dist_func=FunctionWrapper (\n distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)\n )\n maxlen=1000\n warm_up=500\n max_candidates=50\n delta=0.0001\n prune_prob=0.\n n_iters=10\n seed=None\n )\n weighted=True\n cleanup_every=0\n softmax=False\n )\n)",
"ADWIN Bagging": "[HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n)]",
"AdaBoost": "[HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n)]",
"Bagging": "[HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n)]",
"Leveraging Bagging": "[HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n)]",
"Stacking": "[Pipeline (\n StandardScaler (\n with_std=True\n ),\n SoftmaxRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=CrossEntropy (\n class_weight={}\n )\n l2=0\n )\n), GaussianNB (), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), Pipeline (\n StandardScaler (\n with_std=True\n ),\n KNNClassifier (\n n_neighbors=5\n engine=SWINN (\n graph_k=20\n dist_func=FunctionWrapper (\n distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)\n )\n maxlen=1000\n warm_up=500\n max_candidates=50\n delta=0.0001\n prune_prob=0.\n n_iters=10\n seed=None\n )\n weighted=True\n cleanup_every=0\n softmax=False\n )\n)]",
"Voting": "VotingClassifier (\n models=[Pipeline (\n StandardScaler (\n with_std=True\n ),\n SoftmaxRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=CrossEntropy (\n class_weight={}\n )\n l2=0\n )\n), GaussianNB (), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), Pipeline (\n StandardScaler (\n with_std=True\n ),\n KNNClassifier (\n n_neighbors=5\n engine=SWINN (\n graph_k=20\n dist_func=FunctionWrapper (\n distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)\n )\n maxlen=1000\n warm_up=500\n max_candidates=50\n delta=0.0001\n prune_prob=0.\n n_iters=10\n seed=None\n )\n weighted=True\n cleanup_every=0\n softmax=False\n )\n)]\n use_probabilities=True\n)",
"[baseline] Last Class": "NoChangeClassifier ()"
}
},
"Multiclass classification": {
"Dataset": {
"ImageSegments": "Image segments classification.\n\nThis dataset contains features that describe image segments into 7 classes: brickface, sky,\nfoliage, cement, window, path, and grass.\n\n Name ImageSegments \n Task Multi-class classification \n Samples 2,310 \nFeatures 18 \n Classes 7 \n Sparse False \n Path /Users/mastelini/miniconda3/envs/river-benchmark/lib/python3.10/site-packages/river/datasets/segment.csv.zip",
"Insects": "Insects dataset.\n\nThis dataset has different variants, which are:\n\n- abrupt_balanced\n- abrupt_imbalanced\n- gradual_balanced\n- gradual_imbalanced\n- incremental-abrupt_balanced\n- incremental-abrupt_imbalanced\n- incremental-reoccurring_balanced\n- incremental-reoccurring_imbalanced\n- incremental_balanced\n- incremental_imbalanced\n- out-of-control\n\nThe number of samples and the difficulty change from one variant to another. The number of\nclasses is always the same (6), except for the last variant (24).\n\n Name Insects \n Task Multi-class classification \n Samples 52,848 \n Features 33 \n Classes 6 \n Sparse False \n Path /Users/mastelini/river_data/Insects/INSECTS-abrupt_balanced_norm.arff \n URL http://sites.labic.icmc.usp.br/vsouza/repository/creme/INSECTS-abrupt_balanced_norm.arff\n Size 15.66 MB \nDownloaded True \n Variant abrupt_balanced \n\nParameters\n----------\n variant\n Indicates which variant of the dataset to load.",
"Keystroke": "CMU keystroke dataset.\n\nUsers are tasked to type in a password. The task is to determine which user is typing in the\npassword.\n\nThe only difference with the original dataset is that the \"sessionIndex\" and \"rep\" attributes\nhave been dropped.\n\n Name Keystroke \n Task Multi-class classification \n Samples 20,400 \n Features 31 \n Classes 51 \n Sparse False \n Path /Users/mastelini/river_data/Keystroke/DSL-StrongPasswordData.csv\n URL http://www.cs.cmu.edu/~keystroke/DSL-StrongPasswordData.csv \n Size 4.45 MB \nDownloaded True "
},
"Model": {
"Naive Bayes": "GaussianNB ()",
"Hoeffding Tree": "HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n)",
"Hoeffding Adaptive Tree": "HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=True\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=42\n)",
"Adaptive Random Forest": "[]",
"Aggregated Mondrian Forest": "[]",
"Streaming Random Patches": "SRPClassifier (\n model=HoeffdingTreeClassifier (\n grace_period=50\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=0.01\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n )\n n_models=10\n subspace_size=0.6\n training_method=\"patches\"\n lam=6\n drift_detector=ADWIN (\n delta=1e-05\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n warning_detector=ADWIN (\n delta=0.0001\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n disable_detector=\"off\"\n disable_weighted_vote=False\n seed=None\n metric=Accuracy (\n cm=ConfusionMatrix (\n classes=[]\n )\n )\n)",
"k-Nearest Neighbors": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n KNNClassifier (\n n_neighbors=5\n engine=SWINN (\n graph_k=20\n dist_func=FunctionWrapper (\n distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)\n )\n maxlen=1000\n warm_up=500\n max_candidates=50\n delta=0.0001\n prune_prob=0.\n n_iters=10\n seed=None\n )\n weighted=True\n cleanup_every=0\n softmax=False\n )\n)",
"ADWIN Bagging": "[HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n)]",
"AdaBoost": "[HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n)]",
"Bagging": "[HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n), HoeffdingAdaptiveTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n)]",
"Leveraging Bagging": "[HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n)]",
"Stacking": "[Pipeline (\n StandardScaler (\n with_std=True\n ),\n SoftmaxRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=CrossEntropy (\n class_weight={}\n )\n l2=0\n )\n), GaussianNB (), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), Pipeline (\n StandardScaler (\n with_std=True\n ),\n KNNClassifier (\n n_neighbors=5\n engine=SWINN (\n graph_k=20\n dist_func=FunctionWrapper (\n distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)\n )\n maxlen=1000\n warm_up=500\n max_candidates=50\n delta=0.0001\n prune_prob=0.\n n_iters=10\n seed=None\n )\n weighted=True\n cleanup_every=0\n softmax=False\n )\n)]",
"Voting": "VotingClassifier (\n models=[Pipeline (\n StandardScaler (\n with_std=True\n ),\n SoftmaxRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=CrossEntropy (\n class_weight={}\n )\n l2=0\n )\n), GaussianNB (), HoeffdingTreeClassifier (\n grace_period=200\n max_depth=inf\n split_criterion=\"info_gain\"\n delta=1e-07\n tau=0.05\n leaf_prediction=\"nba\"\n nb_threshold=0\n nominal_attributes=None\n splitter=GaussianSplitter (\n n_splits=10\n )\n binary_split=False\n min_branch_fraction=0.01\n max_share_to_split=0.99\n max_size=100.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n), Pipeline (\n StandardScaler (\n with_std=True\n ),\n KNNClassifier (\n n_neighbors=5\n engine=SWINN (\n graph_k=20\n dist_func=FunctionWrapper (\n distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)\n )\n maxlen=1000\n warm_up=500\n max_candidates=50\n delta=0.0001\n prune_prob=0.\n n_iters=10\n seed=None\n )\n weighted=True\n cleanup_every=0\n softmax=False\n )\n)]\n use_probabilities=True\n)",
"[baseline] Last Class": "NoChangeClassifier ()"
}
},
"Regression": {
"Dataset": {
"ChickWeights": "Chick weights along time.\n\nThe stream contains 578 items and 3 features. The goal is to predict the weight of each chick\nalong time, according to the diet the chick is on. The data is ordered by time and then by\nchick.\n\n Name ChickWeights \n Task Regression \n Samples 578 \nFeatures 3 \n Sparse False \n Path /Users/mastelini/miniconda3/envs/river-benchmark/lib/python3.10/site-packages/river/datasets/chick-weights.csv",
"TrumpApproval": "Donald Trump approval ratings.\n\nThis dataset was obtained by reshaping the data used by FiveThirtyEight for analyzing Donald\nTrump's approval ratings. It contains 5 features, which are approval ratings collected by\n5 polling agencies. The target is the approval rating from FiveThirtyEight's model. The goal of\nthis task is to see if we can reproduce FiveThirtyEight's model.\n\n Name TrumpApproval \n Task Regression \n Samples 1,001 \nFeatures 6 \n Sparse False \n Path /Users/mastelini/miniconda3/envs/river-benchmark/lib/python3.10/site-packages/river/datasets/trump_approval.csv.gz"
},
"Model": {
"Linear Regression": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n)",
"Linear Regression with l1 regularization": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=1.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n)",
"Linear Regression with l2 regularization": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=1.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n)",
"Passive-Aggressive Regressor, mode 1": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n PARegressor (\n C=1.\n mode=1\n eps=0.1\n learn_intercept=True\n )\n)",
"Passive-Aggressive Regressor, mode 2": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n PARegressor (\n C=1.\n mode=2\n eps=0.1\n learn_intercept=True\n )\n)",
"k-Nearest Neighbors": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n KNNRegressor (\n n_neighbors=5\n engine=SWINN (\n graph_k=20\n dist_func=FunctionWrapper (\n distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)\n )\n maxlen=1000\n warm_up=500\n max_candidates=50\n delta=0.0001\n prune_prob=0.\n n_iters=10\n seed=None\n )\n aggregation_method=\"mean\"\n )\n)",
"Hoeffding Tree": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n HoeffdingTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n )\n)",
"Hoeffding Adaptive Tree": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=True\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=42\n )\n)",
"Stochastic Gradient Tree": "SGTRegressor (\n delta=1e-07\n grace_period=200\n init_pred=0.\n max_depth=inf\n lambda_value=0.1\n gamma=1.\n nominal_attributes=[]\n feature_quantizer=StaticQuantizer (\n n_bins=64\n warm_start=100\n buckets=None\n )\n)",
"Adaptive Random Forest": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n []\n)",
"Aggregated Mondrian Forest": "[]",
"Adaptive Model Rules": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n AMRules (\n n_min=200\n delta=1e-07\n tau=0.05\n pred_type=\"adaptive\"\n pred_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n splitter=TEBSTSplitter (\n digits=1\n )\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n fading_factor=0.99\n anomaly_threshold=-0.75\n m_min=30\n ordered_rule_set=True\n min_samples_split=5\n )\n)",
"Streaming Random Patches": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n SRPRegressor (\n model=HoeffdingTreeRegressor (\n grace_period=50\n max_depth=inf\n delta=0.01\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n )\n n_models=10\n subspace_size=0.6\n training_method=\"patches\"\n lam=6\n drift_detector=ADWIN (\n delta=1e-05\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n warning_detector=ADWIN (\n delta=0.0001\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n disable_detector=\"off\"\n disable_weighted_vote=True\n drift_detection_criteria=\"error\"\n aggregation_method=\"mean\"\n seed=42\n metric=MAE ()\n )\n)",
"Bagging": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n [HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n ), HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n ), HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n ), HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n ), HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n ), HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n ), HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n ), HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n ), HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n ), HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=False\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n )]\n)",
"Exponentially Weighted Average": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n [LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n ), HoeffdingAdaptiveTreeRegressor (\n grace_period=200\n max_depth=inf\n delta=1e-07\n tau=0.05\n leaf_prediction=\"adaptive\"\n leaf_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n model_selector_decay=0.95\n nominal_attributes=None\n splitter=TEBSTSplitter (\n digits=1\n )\n min_samples_split=5\n bootstrap_sampling=True\n drift_window_threshold=300\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n switch_significance=0.05\n binary_split=False\n max_size=500.\n memory_estimate_period=1000000\n stop_mem_management=False\n remove_poor_attrs=False\n merit_preprune=True\n seed=None\n ), KNNRegressor (\n n_neighbors=5\n engine=SWINN (\n graph_k=20\n dist_func=FunctionWrapper (\n distance_function=functools.partial(<function minkowski_distance at 0x1380aa200>, p=2)\n )\n maxlen=1000\n warm_up=500\n max_candidates=50\n delta=0.0001\n prune_prob=0.\n n_iters=10\n seed=None\n )\n aggregation_method=\"mean\"\n ), AMRules (\n n_min=200\n delta=1e-07\n tau=0.05\n pred_type=\"adaptive\"\n pred_model=LinearRegression (\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.01\n )\n )\n loss=Squared ()\n l2=0.\n l1=0.\n intercept_init=0.\n intercept_lr=Constant (\n learning_rate=0.01\n )\n clip_gradient=1e+12\n initializer=Zeros ()\n )\n splitter=TEBSTSplitter (\n digits=1\n )\n drift_detector=ADWIN (\n delta=0.002\n clock=32\n max_buckets=5\n min_window_length=5\n grace_period=10\n )\n fading_factor=0.99\n anomaly_threshold=-0.75\n m_min=30\n ordered_rule_set=True\n min_samples_split=5\n )]\n)",
"River MLP": "Pipeline (\n StandardScaler (\n with_std=True\n ),\n MLPRegressor (\n hidden_dims=(5,)\n activations=(<class 'river.neural_net.activations.ReLU'>, <class 'river.neural_net.activations.ReLU'>, <class 'river.neural_net.activations.Identity'>)\n loss=Squared ()\n optimizer=SGD (\n lr=Constant (\n learning_rate=0.001\n )\n )\n seed=42\n )\n)",
"[baseline] Mean predictor": "StatisticRegressor (\n statistic=Mean ()\n)"
}
}
}