a Java toolkit for training, testing, and applying Bayesian Network Classifiers. Implemented classifiers have been shown to perform well in a variety of artificial intelligence, machine learning, and data mining applications. -a Java toolkit for tra

Bayesian Network Classifiers In Weka

这是matlab编写的3个常用机器学习分类器代码。其中包括了： 1）PCA 分类其；2）LDA分类器：3）naive贝叶斯分类器。 3个算法的实现参考了《Introduction to Machine Learning》。 除了这3个分类算法的实现外，代码里面还包含了用于测试的main.m 主程序和一个实验的简要报告。实验在著名数据集acoustic_train_data 上进行。-This source code includes the implementation of three f

模式识别 北京大学 本科生课程 课件 （包括贝叶斯模型、最近邻、SVM、线性与非线性分类器、boosting、统计学习、非监督学习等）-Pattern Recognition Peking University Courseware (including Bayesian model, the nearest neighbor, SVM, linear and non-linear classifiers, boosting, statistical learning, unsupervised