资源列表
HK.rar
- H-K(Ho-Kashyap)算法。在模式识别应用中运用HK算法根据样本进行分类器训练。,HK (Ho-Kashyap) algorithm. Applications in pattern recognition algorithm based on the use of HK classifier training samples.
BayesClassifier.rar
- 贝叶斯分类算法，构造朴素贝叶斯分类器，对给定的中文文本进行分类,Bayesian classification algorithm, Naive Bayes classifier structure of a given Chinese text classification
Clustering.zip
- 数据挖掘算法的实现，基于模糊聚类的最大树算法，数据集是darpa99,也就是KDD-CUP99中采用的数据集,The realization of data mining algorithms, based on fuzzy clustering of the largest tree algorithm, a data set is darpa99, which is used in KDD-CUP99 data set
KPCA_SVM_Train.rar
- 能够对输入的三维数据进行pca分析 然后输出主要的两位下的图像的坐标,the code could do pca analysis for a 3D data, and out put the first two main dimention of these data.
lpp.rar
- 一种很重要的非监督降维方法，是流形学习算法Laplacian Eigenmap 的线性化方法，在人脸识别中效果非常好。,A very important method of unsupervised dimensionality reduction, manifold learning algorithm is Laplacian Eigenmap linearization method is very effective in face recognition.
ChatBots.rar
- 一个关于制作聊天机器人的文章，里面涵盖了一些算法和著名的ALICE机器人的工作原理讲解，希望可以给想研究人工智能的朋友们带来一点帮助。,An article about the chatbot, there are some arithmetic inside it, and also talk something about ALICE bot, wish give some help to the person who is interested in AI.
adaboost.rar
- 一个最基本的adaboost算法源码（matlab）,a basic adaboost algorithom source code (matlab)
gp99.rar
- 股票软件源代码,含K线控件。简单分析与使用。,Shares of software source code, including K-line control. With the use of a simple analysis.
Neuro-Fuzzy_and_Soft_Computing
- 張智星先生的代表作，Amazon的介紹：http://www.amazon.com/Neuro-Fuzzy-Soft-Computing-Computational-Intelligence/dp/0132610663,This book is suitable as a self-study guide by researchers who want to learn basic and advanced neuro-fuzzy and soft computing within the fr
BPN-GA.rar
- 用于神经网络训练的混合遗传算法，与快速BP算法结合。,For neural network training, hybrid genetic algorithm, combined with the rapid BP algorithm.
svm-light.rar
- 基于matlab的SVM一个很不错的工具箱,matlab svm source code toolbox
paes.rar
- 多目标遗传算法PESA程序的selection程序，网上没有PESA的完整程序，这个也是好不容易找到的。效果据说强于NSGA和SPE。,the selection function of PESA. It is said in some literature that the resutlts are good than NSGA and SPEA