User:Heinkeqq/Books/Statistical Learning Theory

Statistical Learning Theory

 * Introduction
 * Statistical learning theory


 * Basics
 * Characteristic function (probability theory)
 * Linear separability
 * Concept class
 * Probability density function
 * Expected value
 * Hyperplane
 * Linear classifier


 * The three Main Learning Problems
 * Regression analysis
 * Pattern recognition
 * Density estimation


 * Learning Techniques
 * Supervised learning
 * Unsupervised learning


 * Machine Learning
 * Machine learning
 * Reinforcement learning
 * Online machine learning
 * Statistical classification


 * PAC Learning
 * Probably approximately correct learning


 * Vapnik-Chervonenkis Theory
 * Vapnik–Chervonenkis theory
 * VC dimension


 * Perceptron Learning
 * Perceptron
 * Feedforward neural network
 * Backpropagation
 * Sauer–Shelah lemma
 * Support vector machine
 * Bayesian inference
 * Algorithmic learning theory