This repository contains my codes and answers to the Data Mining course homework which I passed in Isfahan University of Technology. In this course we learned about Data science methodology which is shown below. We worked with several datasets for more comprehention as well.
This Homework focused on preprocessing and Exploratory Data Analysis (EDA).
- Question 2: Student's dataset analysis and exploration
- Question 3: Working with Machines dataset and exploring it
- Question 4: Checking whether the Machines dataset is balanced or imbalanced
- Question 5: Finding outliers and removing them in Machines Dataset
- Question 6: Binning CACH column in the Dataset
- Question 7:Exploring Kaggle Titanic Dataset
The aim of this homework is again EDA and setup phase
- Question 1: Exploratory data Analysis for credit card dataset
- Question 2: Exploratory data Analysis for Heart Disease dataset
- Question 3: Overlay charts
- Question 4: Binning based on predictive variable
- Question 5: Whole methodology on titanic dataset
This homework main focus was on modelling phase (Supervised Learning). In addition I worked with fuzzy rule-based systems as an extra part of this homework.
- Question 1: Working with neural networks
- Question 2: Feature Selection
- Question 3: Naive Bayes
- Question 4: Regressions
- Question 5: Poisson Regression
- Question 6: Implementing KNN algorithm
- Question 7: SVM
- Question 8: Dimention Reduction
- Question 9: Ensemble models: AdaBoost
- Question 10: Ensemble models: XGBoost
- Question 11: Ensemble models: Stacking Classifier
This homework focused on unsupervised learning
- Question 1: Kmeans Clustering Algorithm
- Question 2: Agglomerative Clustering
- Question 3: DBSCAN algorithm
This homework focused on Association rule mining
- Question 1: Association Rules using mlxtend library
- Question 2: Advanced association rules
- Question 3: Sequence Pattern Mining usging gsppy algorithm