Machine Learning Algorithm Visualizer

A visualizer for some common machine learning algorithms covered in UC Berkeley's CS189: Introduction to Machine Learning course.

Linear Discriminant
Analysis (LDA)

Quadratic Discriminant Analysis (QDA)

Logistic Regression

Decision Tree

Random Decision Tree

Dataset Parameters

Noise:

Samples:

This visualizer was created by Jeffrey Kim, a student studying Electrical Engineering and Computer Science at the University of California, Berkeley.
It randomly creates 3 datasets using the selected parameters and trains each model on every dataset. It then generates the corresponding heatmaps using the posterior probabilities of each model.

Check out the source code or my other public github projects!
Here's also the link to my personal website!