Tag
feature-scaling
- Aug 19, 2026 What a Distance Function Decides About Cluster Shape Squared Euclidean, cosine, Mahalanobis, and set distances each impose a different notion of similarity, and the choice fixes which clusters are available before any algorithm runs. machine learning
- Jul 5, 2026 Feature Scaling and the Conditioning of Gradient Descent How per-feature magnitude sets the condition number of a loss surface, why that number fixes the iteration count of first-order methods, and what each scaler costs. machine learning
- Jun 12, 2026 Principal Component Analysis Through the Singular Value Decomposition Maximizing projected variance, minimizing reconstruction error, and decorrelating features all select the same subspace, and the SVD computes it without ever forming the covariance matrix. machine learning
- Apr 29, 2025 Mean Imputation and the Variance It Removes Substituting the column mean for a missing value preserves the mean exactly and shrinks the variance and the covariance, changing coefficients, standard errors, and fit. machine learning