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🧠 Supervised Learning Algorithms

A practical tour of supervised learning algorithms, from linear regression to ensemble methods, with guidance on when to use each.

AI & Machine Learning3DAdvanced60 FPS

A 3D decision-surface landscape lets you watch logistic regression, k-nearest neighbors, a decision tree, and a random forest carve up the same labelled dataset in very different ways.

🔬 What It Demonstrates

Every point of the plane gets a predicted probability rendered as terrain height and colour. Training spheres sit at their true class height, so a sphere floating over the "wrong" colour is a visible misclassification — no confusion matrix required.

🎮 How to Use

Pick an algorithm and a dataset shape, then push the complexity slider from an underfit flat landscape to an overfit jagged one. Add label noise to see which algorithms chase it and which stay smooth.

💡 Did You Know?

Random forests were popularised by Leo Breiman in 2001. By averaging many high-variance trees trained on bootstrap samples, they trade a little bias for a large reduction in variance — usually a good deal.

⚙ Under the hood

A practical tour of supervised learning algorithms, from linear regression to ensemble methods, with guidance on when to use each.

machine learningsupervised learningalgorithmsdata scienceregressionensemble methodsThree.js

3D · Three.js / WebGL renderer · 60 FPS target · runs fully client-side, no install