ML course

A collection of basic machine learning algorithms taught to students of the CS major. All assignments are implemented in R.

Contents

Metric classifiers

• 1-NN Algorithm
• Leave-one-out CV for iris features 1-4
• Nearest neighbors algorithms
• Parzen window
• Potential functions
• STOLP

Metric classifiers comparison table

Bayesian classifiers

• Contour lines of the Gaussian distribution PDF
• Naive normal bayesian classifier
• Plug-in algorithm
• Linear Fisher's discriminant

Linear classifiers

• SGD, Adaline and perceptron / Hebb's rule
• Logistic regression
• Support vector machine