1 Density Estimation 2 Histogram Method 3 Parzen Window 4 k-nearest neighbors 5 Summary of nonparametric models

1 Probability Density Estimation 2 Maximum Likelihood Estimation 3 MAP estimation 4 Bayesian estimation 5 Expectation maximization

1 Basic principle 2 Multiple classifier combination 3 Bagging 4 Boosting

1 History 2 Preparatory knowledge 3 XOR problem 4 MLP is doing what? 5 Tilling Algorithm 6 Learning algorithm for MLP of differentiable activation function

1 A problem in perceptron 2 Linear SVM in LSC 3 SVM in LIC 4 Kernel Functions 5 Nonlinear SVM 6 SMO Algorithm

1 Preparatory knowledge 2 Perceptron concept 3 Learning strategies of perceptron 4 Perceptron learning algorithm 5 Convergence of perceptron learning algorithm 6 Dual form of perceptron learning algorithm

1 A Case 2 Least Squares Method 3 From Linear to Nonlinear: Using Linear Model 4 How Regression Got Its Name 5 Probability Interpretation 6 Bias–Variance Dilemma

1 Linear Algebra Notations and Fundamental Concepts Matrix Multiplication Operational Properties Linear Space Quadratic Form and Positive Definite Matrix Matrix Calculus 2 Probability Theory Probability Space Random Variable and Its Distribution Numerical Characteristics of Random Variables Conditional Expectation Jenson’s Inequality

1 Definition of Statistical Learning 2 Application Case of Statistical Pattern Recognition 3 SPR System Framework and Design Cycle 4 Basic Concepts 5 Machine Learning in Different AI Disciplines

对外经济贸易大学：《应用统计 Applied Statistics》课程教学资源（教案讲稿）