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Diff for: ‎experimentation/alg_datasets/0.05_DecisionTreeClassifier.csv

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datasets,DecisionTreeClassifier:ENANE,DecisionTreeClassifier:ENN,DecisionTreeClassifier:LSSm,DecisionTreeClassifier:base
2+
BreastTissue.csv,0.24727272727272726,0.2627272727272727,0.26090909090909087,0.31909090909090904
3+
Modeling.csv,0.4976923076923077,0.5283076923076923,0.5567692307692307,0.5718461538461539
4+
SPECTF.csv,0.375,0.5125,0.5972222222222222,0.525
5+
ThoraricSurgery.csv,0.7659574468085106,0.7659574468085106,0.7489361702127659,0.6936170212765957
6+
blood-transfusion.csv,0.7137837837837837,0.6578738738738739,0.6805765765765766,0.6938918918918919
7+
dermatology.csv,0.035735735735735706,0.01899399399399397,0.04677177177177174,0.07087087087087084
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ecoli.csv,0.10677361853832439,0.10401069518716573,0.07406417112299463,0.1137254901960784
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glass.csv,0.13658008658008652,0.13549783549783545,0.16904761904761897,0.11233766233766229
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imageSegmentation.csv,0.21904761904761902,0.20476190476190476,0.29047619047619044,0.29999999999999993
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indian-liver.csv,0.1873173582700175,0.19549970777323203,0.20876680303915837,0.174926943308007
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ionosphere.csv,0.7018253968253968,0.7322222222222223,0.7548412698412699,0.7148412698412698
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letter-recognition.csv,0.31625000000000003,0.31745,0.31074999999999997,0.31710000000000005
14+
liver.csv,0.20554621848739493,0.23470588235294115,0.2110084033613445,0.2290756302521008
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pendigits.csv,0.8011770360480641,0.8018365821094793,0.8103814864263462,0.7994362260792167
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satimage.csv,0.044945567651632934,0.04090202177293931,0.040435458786936204,0.04276827371695175
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sonar.csv,0.5623809523809523,0.6002380952380952,0.6542857142857142,0.5828571428571429
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wholesaleCustomers.csv,0.09318181818181814,0.06363636363636359,0.09090909090909087,0.07045454545454544
19+
wifi-localization.csv,0.044,0.0445,0.06,0.0475

Diff for: ‎experimentation/alg_datasets/0.05_GaussianNB.csv

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@@ -0,0 +1,19 @@
1+
datasets,GaussianNB:ENANE,GaussianNB:ENN,GaussianNB:LSSm,GaussianNB:base
2+
BreastTissue.csv,0.22545454545454544,0.19727272727272727,0.1709090909090909,0.24636363636363634
3+
Modeling.csv,0.4478461538461539,0.4035384615384615,0.46415384615384614,0.5293846153846153
4+
SPECTF.csv,0.5,0.5,0.4875,0.5125
5+
ThoraricSurgery.csv,0.5765957446808511,0.5085106382978724,0.6127659574468085,0.5255319148936171
6+
blood-transfusion.csv,0.7044144144144144,0.7005225225225226,0.7325405405405405,0.6951711711711711
7+
dermatology.csv,0.02980480480480478,0.035660660660660634,0.02762762762762761,0.02477477477477475
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ecoli.csv,0.12433155080213902,0.008912655971479489,0.02388591800356504,0.05044563279857396
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glass.csv,0.13030303030303028,0.14090909090909087,0.1409090909090909,0.18636363636363634
10+
imageSegmentation.csv,0.1904761904761904,0.19999999999999996,0.1904761904761904,0.219047619047619
11+
indian-liver.csv,0.39593804792518994,0.3601110461718293,0.4374926943308006,0.3664815897136178
12+
ionosphere.csv,0.7124603174603175,0.704047619047619,0.6923015873015873,0.6954761904761905
13+
letter-recognition.csv,0.2049,0.20350000000000001,0.20139999999999997,0.21070000000000003
14+
liver.csv,0.18504201680672266,0.2173109243697479,0.2399159663865546,0.2580672268907563
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pendigits.csv,0.7481965287049399,0.7321846016911437,0.7499400089007565,0.7188348909657322
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satimage.csv,0.03483670295489888,0.03374805598755829,0.03250388802488333,0.03483670295489888
17+
sonar.csv,0.5914285714285714,0.5769047619047619,0.5521428571428572,0.5764285714285714
18+
wholesaleCustomers.csv,0.14090909090909087,0.16136363636363632,0.10909090909090906,0.2045454545454545
19+
wifi-localization.csv,0.037,0.037,0.0335,0.033

Diff for: ‎experimentation/alg_datasets/0.05_KNeighborsClassifier.csv

+19
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@@ -0,0 +1,19 @@
1+
datasets,KNeighborsClassifier:ENANE,KNeighborsClassifier:ENN,KNeighborsClassifier:LSSm,KNeighborsClassifier:base
2+
BreastTissue.csv,0.33090909090909093,0.2,0.21818181818181817,0.2627272727272727
3+
Modeling.csv,0.5878461538461538,0.4890769230769231,0.4907692307692308,0.587076923076923
4+
SPECTF.csv,0.5,0.5125,0.5,0.5
5+
ThoraricSurgery.csv,0.8446808510638298,0.7851063829787235,0.8226950354609929,0.8
6+
blood-transfusion.csv,0.761981981981982,0.7378018018018018,0.7190810810810812,0.7312252252252252
7+
dermatology.csv,0.03828828828828828,0.00548048048048047,0.040615615615615594,0.06336336336336335
8+
ecoli.csv,0.14999999999999997,0.08529411764705878,0.04777183600713011,0.026916221033868086
9+
glass.csv,0.07878787878787877,0.12207792207792205,0.10822510822510818,0.12987012987012983
10+
imageSegmentation.csv,0.21904761904761902,0.2952380952380952,0.28095238095238095,0.18095238095238092
11+
indian-liver.csv,0.18535943892460546,0.15958503798947982,0.1645236703682057,0.16277030976037404
12+
ionosphere.csv,0.6296031746031746,0.7495238095238095,0.7353174603174603,0.661031746031746
13+
letter-recognition.csv,0.2945,0.29564999999999997,0.28825,0.29095
14+
liver.csv,0.21512605042016805,0.20008403361344534,0.20302521008403357,0.2642857142857143
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pendigits.csv,0.9115323542501113,0.9093951045838896,0.9109961726746774,0.9116639074321317
16+
satimage.csv,0.0326594090202177,0.03468118195956451,0.02519440124416794,0.032814930015552066
17+
sonar.csv,0.5199999999999999,0.5052380952380953,0.534047619047619,0.5240476190476191
18+
wholesaleCustomers.csv,0.04318181818181815,0.05454545454545451,0.04772727272727269,0.09090909090909087
19+
wifi-localization.csv,0.038,0.0365,0.051500000000000004,0.0345

Diff for: ‎experimentation/alg_datasets/0.15_DecisionTreeClassifier.csv

+19
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@@ -0,0 +1,19 @@
1+
datasets,DecisionTreeClassifier:ENANE,DecisionTreeClassifier:ENN,DecisionTreeClassifier:LSSm,DecisionTreeClassifier:base
2+
BreastTissue.csv,0.5545454545454545,0.4818181818181818,0.5354545454545454,0.44363636363636366
3+
Modeling.csv,0.6613846153846155,0.6187692307692307,0.6498461538461539,0.6393846153846153
4+
SPECTF.csv,0.525,0.5875,0.525,0.6
5+
ThoraricSurgery.csv,0.7680851063829788,0.7638297872340425,0.7702127659574468,0.7617021276595745
6+
blood-transfusion.csv,0.7284684684684685,0.6912252252252252,0.7406306306306306,0.6965765765765766
7+
dermatology.csv,0.00818318318318317,0.0054054054054054005,0.01906906906906904,0.01358858858858857
8+
ecoli.csv,0.04135472370766487,0.06568627450980388,0.12727272727272726,0.11684491978609626
9+
glass.csv,0.08961038961038957,0.14978354978354974,0.0939393939393939,0.12619047619047613
10+
imageSegmentation.csv,0.7095238095238094,0.6476190476190476,0.6285714285714286,0.6714285714285715
11+
indian-liver.csv,0.2040911747516072,0.21943308007013437,0.2557276446522502,0.20420806545879602
12+
ionosphere.csv,0.7776984126984127,0.7807142857142857,0.7945238095238095,0.7805555555555556
13+
letter-recognition.csv,0.3729,0.37324999999999997,0.3765,0.38005
14+
liver.csv,0.25184873949579833,0.22563025210084028,0.2286554621848739,0.1829411764705882
15+
pendigits.csv,0.8697653760569649,0.8756332888295505,0.8799061860258123,0.8717662661326212
16+
satimage.csv,0.032814930015552066,0.03468118195956451,0.03172628304821148,0.03545878693623636
17+
sonar.csv,0.6676190476190476,0.6490476190476191,0.6452380952380953,0.6259523809523809
18+
wholesaleCustomers.csv,0.09772727272727266,0.08409090909090905,0.06818181818181814,0.06136363636363633
19+
wifi-localization.csv,0.0475,0.042499999999999996,0.042499999999999996,0.057999999999999996

Diff for: ‎experimentation/alg_datasets/0.15_GaussianNB.csv

+19
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,19 @@
1+
datasets,GaussianNB:ENANE,GaussianNB:ENN,GaussianNB:LSSm,GaussianNB:base
2+
BreastTissue.csv,0.4163636363636363,0.45999999999999996,0.43090909090909085,0.37727272727272726
3+
Modeling.csv,0.5763076923076923,0.5212307692307692,0.578923076923077,0.5655384615384615
4+
SPECTF.csv,0.6625,0.7,0.65,0.7
5+
ThoraricSurgery.csv,0.4829787234042553,0.31702127659574464,0.2702127659574468,0.4
6+
blood-transfusion.csv,0.7284864864864865,0.7406846846846846,0.7059279279279279,0.7124864864864865
7+
dermatology.csv,0.01358858858858857,0.029954954954954937,0.0054054054054054005,0.016291291291291272
8+
ecoli.csv,0.09188948306595364,0.21951871657754013,0.04162210338680925,0.17201426024955435
9+
glass.csv,0.15389610389610384,0.14069264069264067,0.17229437229437225,0.24220779220779215
10+
imageSegmentation.csv,0.5761904761904761,0.5666666666666667,0.5238095238095237,0.5238095238095238
11+
indian-liver.csv,0.4646697837521917,0.4612507305669199,0.4800993571011104,0.47492694330800705
12+
ionosphere.csv,0.7181746031746032,0.7065873015873015,0.7351587301587301,0.720952380952381
13+
letter-recognition.csv,0.23675000000000002,0.2084,0.22465000000000002,0.2206
14+
liver.csv,0.1587394957983193,0.17428571428571424,0.20226890756302515,0.13310924369747895
15+
pendigits.csv,0.7704792167334223,0.7598057854917668,0.7554129060970183,0.7704811748998666
16+
satimage.csv,0.03328149300155518,0.03343701399688955,0.03390357698289266,0.0326594090202177
17+
sonar.csv,0.6402380952380953,0.6109523809523809,0.5914285714285714,0.6195238095238095
18+
wholesaleCustomers.csv,0.05909090909090904,0.07045454545454541,0.07499999999999994,0.09999999999999996
19+
wifi-localization.csv,0.0305,0.032,0.035,0.032

Diff for: ‎experimentation/alg_datasets/0.15_KNeighborsClassifier.csv

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@@ -0,0 +1,19 @@
1+
datasets,KNeighborsClassifier:ENANE,KNeighborsClassifier:ENN,KNeighborsClassifier:LSSm,KNeighborsClassifier:base
2+
BreastTissue.csv,0.5290909090909091,0.4909090909090909,0.46909090909090906,0.48090909090909084
3+
Modeling.csv,0.7193846153846154,0.6610769230769231,0.6875384615384615,0.7430769230769231
4+
SPECTF.csv,0.5875,0.5125,0.5875,0.5625
5+
ThoraricSurgery.csv,0.8063829787234041,0.8340425531914895,0.8319148936170213,0.8404255319148936
6+
blood-transfusion.csv,0.7245225225225226,0.7447027027027027,0.721945945945946,0.7472972972972973
7+
dermatology.csv,0.0081081081081081,0.0027027027027027003,0.0,0.0027027027027027003
8+
ecoli.csv,0.17959001782531195,0.09313725490196079,0.02397504456327985,0.05900178253119428
9+
glass.csv,0.07943722943722942,0.13138528138528133,0.10865800865800863,0.1108225108225108
10+
imageSegmentation.csv,0.6476190476190476,0.6952380952380952,0.6857142857142857,0.7095238095238094
11+
indian-liver.csv,0.13015780245470482,0.19377556984219751,0.13383985973115134,0.16811805961426066
12+
ionosphere.csv,0.7862698412698412,0.7153174603174604,0.7662698412698413,0.7894444444444445
13+
letter-recognition.csv,0.36319999999999997,0.36475,0.36088888888888887,0.35855
14+
liver.csv,0.23134453781512604,0.2372268907563025,0.19386554621848734,0.19084033613445375
15+
pendigits.csv,0.9500961281708946,0.9458248331108144,0.9499587004895416,0.9488923898531375
16+
satimage.csv,0.02426127527216172,0.02519440124416794,0.0248833592534992,0.027527216174183487
17+
sonar.csv,0.6492857142857142,0.5773809523809523,0.6497619047619048,0.6016666666666667
18+
wholesaleCustomers.csv,0.0454545454545454,0.04772727272727269,0.04318181818181815,0.06590909090909089
19+
wifi-localization.csv,0.028500000000000004,0.034,0.034999999999999996,0.028499999999999998

Diff for: ‎experimentation/alg_datasets/0.1_DecisionTreeClassifier.csv

+19
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@@ -0,0 +1,19 @@
1+
datasets,DecisionTreeClassifier:ENANE,DecisionTreeClassifier:ENN,DecisionTreeClassifier:LSSm,DecisionTreeClassifier:base
2+
BreastTissue.csv,0.4381818181818182,0.45999999999999996,0.45999999999999996,0.43636363636363634
3+
Modeling.csv,0.6201538461538461,0.6303076923076923,0.5930769230769231,0.5609230769230769
4+
SPECTF.csv,0.5125,0.5875,0.625,0.65
5+
ThoraricSurgery.csv,0.7531914893617021,0.7659574468085106,0.7404255319148936,0.727659574468085
6+
blood-transfusion.csv,0.6950630630630631,0.6899459459459459,0.6910090090090091,0.6926306306306307
7+
dermatology.csv,0.0081081081081081,0.01358858858858857,0.029804804804804786,0.01929429429429428
8+
ecoli.csv,0.14937611408199641,0.12424242424242422,0.06550802139037432,0.04714795008912654
9+
glass.csv,0.1599567099567099,0.0755411255411255,0.12207792207792204,0.13506493506493503
10+
imageSegmentation.csv,0.5238095238095238,0.5523809523809524,0.5285714285714286,0.5047619047619047
11+
indian-liver.csv,0.18544710695499705,0.20064289888953826,0.20917592051431905,0.1885739333722969
12+
ionosphere.csv,0.788968253968254,0.7775396825396825,0.7666666666666667,0.7668253968253969
13+
letter-recognition.csv,0.35259999999999997,0.35575,0.3519,0.35185
14+
liver.csv,0.2430252100840336,0.19428571428571426,0.24638655462184872,0.21999999999999997
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pendigits.csv,0.8506801958166443,0.8486791277258566,0.8514835781041388,0.8546768135291499
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satimage.csv,0.041213063763608046,0.037013996889580056,0.04167962674961116,0.04090202177293931
17+
sonar.csv,0.6002380952380952,0.562142857142857,0.6783333333333333,0.6057142857142856
18+
wholesaleCustomers.csv,0.08636363636363634,0.0886363636363636,0.04999999999999995,0.07727272727272724
19+
wifi-localization.csv,0.052500000000000005,0.0485,0.0415,0.0495

Diff for: ‎experimentation/alg_datasets/0.1_GaussianNB.csv

+19
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,19 @@
1+
datasets,GaussianNB:ENANE,GaussianNB:ENN,GaussianNB:LSSm,GaussianNB:base
2+
BreastTissue.csv,0.3645454545454545,0.3054545454545455,0.24999999999999994,0.35
3+
Modeling.csv,0.5912307692307692,0.5947692307692307,0.604,0.5372307692307692
4+
SPECTF.csv,0.55,0.6375,0.525,0.5125
5+
ThoraricSurgery.csv,0.3893617021276595,0.451063829787234,0.4212765957446808,0.33191489361702126
6+
blood-transfusion.csv,0.7166486486486486,0.6871531531531532,0.721963963963964,0.7113333333333334
7+
dermatology.csv,0.0243243243243243,0.02755255255255253,0.02469969969969968,0.04099099099099097
8+
ecoli.csv,0.061942959001782504,0.03270944741532976,0.06809269162210337,0.023796791443850253
9+
glass.csv,0.16493506493506488,0.20541125541125535,0.2199134199134199,0.17099567099567098
10+
imageSegmentation.csv,0.3904761904761904,0.37619047619047613,0.3666666666666666,0.33809523809523806
11+
indian-liver.csv,0.4546171829339567,0.46648158971361775,0.4354178842781999,0.4354178842781999
12+
ionosphere.csv,0.7323015873015872,0.718015873015873,0.7069047619047619,0.7095238095238094
13+
letter-recognition.csv,0.2222,0.2277,0.21000000000000002,0.21109999999999998
14+
liver.csv,0.2692436974789916,0.15428571428571428,0.23386554621848737,0.1536974789915966
15+
pendigits.csv,0.7521967067200712,0.747666577659101,0.7551394748553627,0.749000267022697
16+
satimage.csv,0.03499222395023325,0.03125972006220837,0.03172628304821148,0.032814930015552066
17+
sonar.csv,0.5961904761904762,0.5919047619047619,0.5966666666666667,0.5823809523809523
18+
wholesaleCustomers.csv,0.07727272727272724,0.08863636363636362,0.11590909090909088,0.08636363636363634
19+
wifi-localization.csv,0.0345,0.0335,0.0375,0.0335

Diff for: ‎experimentation/alg_datasets/0.1_KNeighborsClassifier.csv

+19
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@@ -0,0 +1,19 @@
1+
datasets,KNeighborsClassifier:ENANE,KNeighborsClassifier:ENN,KNeighborsClassifier:LSSm,KNeighborsClassifier:base
2+
BreastTissue.csv,0.4581818181818182,0.4536363636363636,0.3872727272727272,0.36454545454545456
3+
Modeling.csv,0.6803076923076923,0.6772307692307692,0.6843076923076923,0.6387692307692308
4+
SPECTF.csv,0.525,0.5375,0.6125,0.625
5+
ThoraricSurgery.csv,0.8,0.8148936170212766,0.8340425531914895,0.8404255319148936
6+
blood-transfusion.csv,0.7433333333333334,0.7393693693693694,0.7406306306306306,0.7365045045045046
7+
dermatology.csv,0.0027027027027027003,0.0054054054054054005,0.0054054054054054005,0.0
8+
ecoli.csv,0.1368983957219251,0.1839572192513369,0.05704099821746879,0.1653297682709447
9+
glass.csv,0.07034632034632031,0.12554112554112548,0.1361471861471861,0.07510822510822508
10+
imageSegmentation.csv,0.4428571428571428,0.49523809523809526,0.6047619047619047,0.42857142857142855
11+
indian-liver.csv,0.15274693161893627,0.16627703097603738,0.16306253652834596,0.22139099941554644
12+
ionosphere.csv,0.7748412698412699,0.7861111111111112,0.7718253968253969,0.7461904761904762
13+
letter-recognition.csv,0.33535,0.33085,0.3418,0.3332
14+
liver.csv,0.24294117647058822,0.2228571428571428,0.19932773109243695,0.16815126050420165
15+
pendigits.csv,0.9384842011570985,0.9390178905206943,0.9388843791722297,0.9380845571873608
16+
satimage.csv,0.02239502332814928,0.024727838258164832,0.032348367029548956,0.025505443234836677
17+
sonar.csv,0.5923809523809525,0.5583333333333333,0.5716666666666665,0.5916666666666666
18+
wholesaleCustomers.csv,0.05909090909090905,0.07272727272727268,0.052272727272727214,0.07045454545454541
19+
wifi-localization.csv,0.0295,0.041999999999999996,0.0335,0.04

Diff for: ‎experimentation/alg_datasets/0.25_DecisionTreeClassifier.csv

+19
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,19 @@
1+
datasets,DecisionTreeClassifier:ENANE,DecisionTreeClassifier:ENN,DecisionTreeClassifier:LSSm,DecisionTreeClassifier:base
2+
BreastTissue.csv,0.5445454545454546,0.5081818181818182,0.5863636363636363,0.5481818181818181
3+
Modeling.csv,0.6506153846153846,0.7427692307692307,0.7206153846153847,0.7001538461538461
4+
SPECTF.csv,0.65,0.6,0.75,0.6875
5+
ThoraricSurgery.csv,0.7723404255319148,0.7468085106382979,0.7638297872340425,0.7574468085106383
6+
blood-transfusion.csv,0.7164324324324325,0.7112792792792793,0.7113873873873874,0.7045585585585585
7+
dermatology.csv,0.024849849849849844,0.00818318318318317,0.016516516516516498,0.0054054054054054005
8+
ecoli.csv,0.03573975044563278,0.21693404634581107,0.07067736185383242,0.14322638146167554
9+
glass.csv,0.10800865800865797,0.07034632034632031,0.14069264069264065,0.10822510822510818
10+
imageSegmentation.csv,0.7857142857142857,0.7857142857142857,0.7571428571428571,0.7380952380952381
11+
indian-liver.csv,0.19894798363530097,0.18872004675628284,0.19891876095850378,0.18007013442431324
12+
ionosphere.csv,0.8488888888888889,0.8319841269841269,0.8207142857142857,0.8488888888888889
13+
letter-recognition.csv,0.39765,0.391,0.4006,0.39245
14+
liver.csv,0.15924369747899153,0.22873949579831931,0.21428571428571427,0.19689075630252098
15+
pendigits.csv,0.8947131286159322,0.8943138406764575,0.896187271918113,0.8973849577214063
16+
satimage.csv,0.03919129082426124,0.033437013996889545,0.03468118195956451,0.03639191290824258
17+
sonar.csv,0.5861904761904762,0.6973809523809524,0.6302380952380953,0.6397619047619048
18+
wholesaleCustomers.csv,0.07727272727272723,0.05909090909090904,0.07727272727272722,0.06363636363636362
19+
wifi-localization.csv,0.0395,0.034,0.041999999999999996,0.047

Diff for: ‎experimentation/alg_datasets/0.25_GaussianNB.csv

+19
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,19 @@
1+
datasets,GaussianNB:ENANE,GaussianNB:ENN,GaussianNB:LSSm,GaussianNB:base
2+
BreastTissue.csv,0.5463636363636364,0.5127272727272727,0.6327272727272727,0.5927272727272727
3+
Modeling.csv,0.6001538461538461,0.5683076923076923,0.5684615384615384,0.5915384615384616
4+
SPECTF.csv,0.775,0.775,0.7125,0.775
5+
ThoraricSurgery.csv,0.24468085106382978,0.28723404255319146,0.3212765957446808,0.2212765957446808
6+
blood-transfusion.csv,0.7367027027027027,0.7433693693693694,0.7407027027027027,0.733963963963964
7+
dermatology.csv,0.00548048048048047,0.00548048048048047,0.0027027027027027003,0.0
8+
ecoli.csv,0.1373440285204991,0.07959001782531193,0.203475935828877,0.0765597147950089
9+
glass.csv,0.14480519480519477,0.18766233766233759,0.24588744588744582,0.17380952380952377
10+
imageSegmentation.csv,0.5857142857142857,0.5809523809523809,0.6238095238095238,0.6
11+
indian-liver.csv,0.4732904734073641,0.4835476329631794,0.47840444184687314,0.49041496201052015
12+
ionosphere.csv,0.701031746031746,0.6924603174603174,0.7064285714285714,0.698015873015873
13+
letter-recognition.csv,0.2375,0.23209999999999997,0.2324,0.22490000000000002
14+
liver.csv,0.1964705882352941,0.17117647058823526,0.2025210084033613,0.09865546218487393
15+
pendigits.csv,0.7776886515353805,0.773814686248331,0.7815620827770361,0.7859615487316421
16+
satimage.csv,0.032814930015552066,0.03452566096423014,0.03328149300155518,0.03437013996889577
17+
sonar.csv,0.595952380952381,0.5873809523809523,0.6011904761904762,0.6302380952380953
18+
wholesaleCustomers.csv,0.05227272727272723,0.06363636363636357,0.05909090909090905,0.06590909090909088
19+
wifi-localization.csv,0.028999999999999998,0.031,0.0305,0.031

Diff for: ‎experimentation/alg_datasets/0.25_KNeighborsClassifier.csv

+19
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@@ -0,0 +1,19 @@
1+
datasets,KNeighborsClassifier:ENANE,KNeighborsClassifier:ENN,KNeighborsClassifier:LSSm,KNeighborsClassifier:base
2+
BreastTissue.csv,0.5827272727272728,0.5572727272727273,0.6027272727272728,0.48
3+
Modeling.csv,0.7350769230769231,0.7038461538461538,0.7467692307692307,0.7232307692307692
4+
SPECTF.csv,0.625,0.575,0.575,0.575
5+
ThoraricSurgery.csv,0.827659574468085,0.8382978723404255,0.8297872340425532,0.823404255319149
6+
blood-transfusion.csv,0.753981981981982,0.7472072072072071,0.737963963963964,0.7445585585585586
7+
dermatology.csv,0.00825825825825824,0.0054054054054054005,0.00825825825825824,0.00548048048048047
8+
ecoli.csv,0.03262032085561496,0.23467023172905527,0.12352941176470589,0.17994652406417114
9+
glass.csv,0.07987012987012984,0.07467532467532464,0.07510822510822507,0.11688311688311685
10+
imageSegmentation.csv,0.7619047619047619,0.7476190476190476,0.7714285714285715,0.7619047619047619
11+
indian-liver.csv,0.14760374050263,0.1338983050847457,0.14742840444184685,0.12694330800701342
12+
ionosphere.csv,0.8148412698412699,0.7152380952380952,0.811984126984127,0.8264285714285714
13+
letter-recognition.csv,0.38130000000000003,0.3887,0.38465,0.3905
14+
liver.csv,0.2545378151260504,0.25193277310924367,0.22857142857142856,0.19999999999999996
15+
pendigits.csv,0.9651704494882065,0.9623706275033378,0.95849826435247,0.9615695594125502
16+
satimage.csv,0.02208398133748054,0.02503888024883357,0.01975116640746499,0.02628304821150853
17+
sonar.csv,0.6304761904761904,0.6449999999999999,0.6735714285714286,0.6821428571428572
18+
wholesaleCustomers.csv,0.052272727272727235,0.04318181818181814,0.038636363636363594,0.04772727272727269
19+
wifi-localization.csv,0.0305,0.038,0.034,0.031

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