说明：the example and toolbox for machine learning（under windows platform）including all the widely used method such as monte carlo method,reinforcement learning method and so on

说明：Paper implementation of A Modifi ed Finite Newton Method for Fast Solution of Large Scale Linear SVMs S. Sathiya Keerthi and Dennis DeCoste Published in Journal of Machine Learning Research - March,2005

说明：Infer.NET is a .NET framework for machine learning. It provides state-of-the-art message-passing algorithms and statistical routines for performing Bayesian inference.

说明：Pattern Recognition and Machine Learning模式分类经典教材

说明：机器学习（英文版） Tom Mitcher的关于机器学习的经典书籍

说明：C#开发的计算机视觉及人工智能领域的一个功能非常强大的类库，包括图像处理库、计算机视觉库、机器学习库、视频处理库等。

说明：uci机器学习数据库关于字符识别的源数据。是字符识别的研究的关键数据来源。包括手写字体和印刷体两类，手写的数字和印刷体的字母。

说明：This file is devoted to learning methods building on kernels, such as the support vector machine.

说明：这里最全完整的adaboost关于torch算法，适合语音的识别等领域，内有详细介绍，参看dods文档。-

说明：ica for machine learning classification neural networks

说明：Data Mining Practical Machine Learning Tools and Techniques

说明：机器学习是人工智能的一个子领域，是人工智能中非常活跃且范围甚广的主要核心研究领域之一，也是现代智能系统的关键环节和瓶颈。机器学习吸取了人工智能、概率统计、计算复杂性理论、控制论、信息论、哲学、生理学、神经生物学等学科的成果，主要关注于开发一些让计算机可以自动学习的技术，并通过经验提高系统自身的性能。本文介绍了机器学习的概念、基本结构和发展，以及各种机器学习方法，包括机械学习、归纳学习、类比学习、解释学习、基于神经网络的学习以及知识发现等，并简单叙述了机器学习的相关算法，包括决策树算法、随机森林算法、人工神经网络算法、SVM算法、Boosting与Bagging算法、关联规则算法、贝叶斯学习算法以及EM算法等，最后还指出了机器学习的应用及其发展趋势。

说明：PCA in (learning machine) java.

说明：决策树,Machine Learning, Tom Mitchell, McGraw Hill,第3章决策树源码

说明：利用weka 做 machine learning

说明：Pattern Analysis is the process of fi nding general relations in a set of data, and forms the core of many disciplines, from neural networks to so-called syn- tactical pattern recognition, from statistical pattern recognition to machine learning and data mining. Applications of pattern analysis range from bioin- formatics to document retrieval.

说明：一些较好的机器学习讲义，里面有最新的信息！要好好看哦！

说明：Implemenation of a variant of the rotation forest (Rodriguez et al., Rotation Forest: a new classifier ensemble method, PAMI 2006) proposed in L. Nanni and A. Lumini, Using ensemble of classifiers in Bioinformatics, in H. Peters and M. Vogel, Machine Learning Research Progress, Nova publisher, 2009

说明：机器学习+Tom+M.+Mitchell《Machine+Learning》之中文版。据我们导师说这是一本很好的人工智能方面的书，希望学习人工智能的可以看看,我刚找到看。

说明：介绍回归问题中高斯过程的应用，C. E. Rasmussen & C. K. I. Williams, Gaussian Processes for Machine Learning,

说明：list of matlab m-files on matlab 7.0. learning , support vector machine and some utility routines : autocorrelation, linearly scale randomize the row order of a matrix

说明：Pattern recognition and machine learning WWW-Exercises solutions

说明：Machine learning book for beginer!

说明：solution mannual of the book-Pattern recognition and machine learning!

说明：AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files

说明：AdaBoost, Adaptive Boosting, is a well-known meta machine learning algorithm that was proposed by Yoav Freund and Robert Schapire. In this project there two main files 1. ADABOOST_tr.m 2. ADABOOST_te.m to traing and test a user-coded learning (classification) algorithm with AdaBoost. A demo file (demo.m) is provided that demonstrates how these two files can be used with a classifier (basic threshold classifier) for two class classification problem.

说明：Data Mining Practical Machine Learning Tools and Techniques

说明：机器学习的经典课件，有助于提高对机器学习算法的理解

说明：Machine Learning [Mc-Graw Hill - Tom Mitchell, 1997] by Tantanoid

说明：PNN又称为概率神经网络,它最初由数学家Specht于1990年提出,后经Master[1995]等不断发展和完善,已成功地应用于机器学习、人工智能、自动控制等众多领域.概率神经网络比多层前馈网络的数学原理简单,且易于实现