More from Math Visualization
Other simulators in this category — or see all 61.
Least Squares Fit
Noisy linear data; fitted slope and intercept with residuals.
Linear Regression: OLS, Ridge, Lasso & R²
Click/drag scatter points; fit y = β₀ + β₁x with OLS, Ridge (L2 on slope), or Lasso (L1 on slope). Spike Δy on the largest |x| point to see outlier sensitivity; compare SSE and R².
K-Means Clustering (Lloyd)
Click to add points, choose k, randomize centroids, then step Lloyd iterations (assign to nearest centroid, update means). Optional Gaussian-mixture demo; watch within-cluster SSE decrease.
DBSCAN Density Clustering
Sliders for ε and minPts on a click-built point set: core / border / noise coloring, optional ε-disks around cores, demo with scattered outliers.
PCA in 2D (principal components & 1D projection)
Click-built cloud: covariance eigenvectors as PC1/PC2 arrows from the mean, optional orthogonal drops to the PC1 line, and a bottom strip of PC1 scores — the standard rank-one projection coordinate.
Decision Tree Classifier (2D toy)
Greedy axis-aligned splits on a click-labeled scatter: compare **Gini** vs **entropy** impurity, max depth, and min-samples-per-leaf; shaded rectangles show leaf decisions, dashed lines show recursive partitions.