Machine Learning in Haskell

Haskell library implementing foundamental machine learning algorithms. Developed for the "Introduction to Machine Learning" course at the University of Trento (2024/2025).

Walkthrough

Each algorithm implemented in this library is organized into 3 files:

• src/AlgorithmName.hs: implementation code
• theory/AlgorithmName.md: mathematical derivation, explanations, proofs
• example/algorithm-name.hs: usage example

To run the examples:

cabal run algorithm-name

Core Foundations

Mathematical Framework for ML
Formal definitions and theoretical basis for all implementations
Source • Theory

Polynomial Regression
Non-linear regression through polynomial basis expansion
Source • Theory • Example

k-Nearest Neighbors
Non parametric classifier
Source • Theory • Example