Tag: classical-ml
Concepts
- Bernoulli, Multinomial and Complement Naive Bayes
- Choosing a Classical Model for Tabular Data
- Complete Separation and Firth's Correction
- Fused Lasso and Total-Variation Penalties
- Gamma and Tweedie Regression
- KD-Trees and Ball Trees
- Kernel Ridge Regression
- Laplace Smoothing for Naive Bayes
- Linear SVM vs Logistic Regression
- Locality-Sensitive Hashing
- Mercer's Condition and Valid Kernels
- Mixture Discriminant Analysis
- Multinomial and Ordinal Logistic Regression
- MARS: Multivariate Adaptive Regression Splines
- Nystrom Approximation and Random Fourier Features
- Oblique Trees and Linear Model Trees
- Pasting, Random Subspaces and Random Patches
- Poisson and Count Regression
- Polynomial Regression and Basis Expansions
- Projection Pursuit Regression
- Random Forest Proximities
- RANSAC and Robust Model Fitting
- Regularized Discriminant Analysis
- Rule Induction and RIPPER
- SCAD and MCP Non-Convex Penalties
- Sequential Minimal Optimization
- Support Vector Regression
- The Representer Theorem