Visualise linear regression, clustering, decision boundaries, and evaluation metrics. Ideal for building core intuition about supervised and unsupervised learning.
Linear Regression Visualizer
Click on the canvas to add data points. The tool will automatically compute the best-fit regression line and calculate: slope (m), intercept (b), and R².
Slope (m): —
Intercept (b): —
R² Score: —
k-Means Clustering Sandbox
Click on the canvas to add points. Choose the number of clusters (k), then click Run k-Means to watch the clustering process unfold.
Decision Boundary Explorer
Click to add points. Left click = Class +1 (Blue) Right click = Class -1 (Red) Press Train to compute a separating hyperplane using a perceptron.
Confusion Matrix Calculator
Enter the classification results below:
Accuracy: —
Precision: —
Recall: —
F1 Score: —