1. Regression:

• Linear Regression
• Ridge Regression
• Lasso Regression
• ElasticNet Regression
• Decision Tree Regression
• Random Forest Regression
• Support Vector Regression (SVR)
• Bayesian Regression
• KNN Regression
• Weight KNN Regression

2. Clustering:

• K-Means
• Hierarchical Clustering
• DBSCAN
• Mean Shift Clustering

3. Classification:

• KNN (with 2 distance metric) ✓
  • uniform KNN ✓
  • distance Weight KNN ✓
• Tree
  • Decision Tree ✓
  • Random Forest ✓
  • Ada boost
• Regression :
  • Logistic Regression
  • Ridge Regression
  • Lasso Regression
  • ElasticNet Regression
• Bayesian
  • Gaussian ✓
  • Multinomial ✓
• Minimum Distance Classifier ✓
• Support Vector Machine (SVM)
• Perceptron ✓
• simple MLP

3. Dimensionality Reduction:

• Principal Component Analysis (PCA)
• Linear Discriminant Analysis (LDA)

4. Normalization data

• sandardScaler ✓
• MinMaxScaler ✓
• MaxAbsScaler ✓
• RobustScaler ✓
• Normalizer ✓

added soon