Common ML algorithms implemented from scratch

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Included algorithms:

Regression:

• Linear regression with $L_2$, $L_1$ and $L_{\infty}$ objectives

Classification:

• Logistic regression for binary classification $y \in \{0,1\}$
• Binomial deviance loss + $L_2$ regularization for binary classification $y \in \{-1,1\}$
• Hinge loss + $L_2$ regularization for binary classification $y \in \{-1,1\}$
• SVM dual form for binary classification $y \in \{-1,1\}$
• Multinomial deviance loss for multiclass classification

Clustering:

• K-means clustering

Dimensionality reduction:

• Principal component analysis (PCA)

Tests demo:

tests/viz.ipynb

Installation:

pip install -r requirements.txt