说明：  全面系统地介绍了统计学习的主要方法，特别是监督学习方法，包括感知机、k近邻法、朴素贝叶斯法、决策树、逻辑斯谛回归与最大熵模型、支持向量机、提升方法、EM算法、隐马尔可夫模型和条件随机场等
(A comprehensive and systematic introduction to the main methods of statistical learning, particularly supervised learning methods, including Perceptron, k nearest neighbor, naive Bayes method, decision tree, logistic regression and maximum entropy models, support vector machines, lifting scheme, EM algorithm, hidden Markov models and conditions with airports)