一个进行数据挖掘的好方法，可以对数据集中的频繁项进行挖掘。但是有一定的缺点，还有需要改进的地方！...

美国麻省理工大学教授人工智能的课件以及课后的习题相关-American University professor of artificial intelligence at MIT courseware and the exercises related to the after-school

高手学习人工智能心得体会。想学习人工智能的可以来-master learning artificial intelligence experiences. Want to study artificial intelligence can s

支持向量机学习源码程序支持向 量机学习源码程序支持向 量机学习源码程序-Support vector machine learning support vector machine learning source program source program source program support vector machine learning support vector machine learning support vector machine learning source program source program

基于改进SVM的特征选择，可以帮助大家认识SVM-To improve the SVM-based feature selection can help you understand the SVM

一个Ｃ编写的足球机器人比赛程序，算法很好-C prepared by a robot soccer competition procedures, a good algorithm

这是一个关于遗传算法的程序，包括了算法的各个过程，其实我对遗传算法也不很懂，也是刚刚开始学习阶段，希望一起进步-This is a genetic algorithm on the procedures, including all the process of the algorithm, in fact, I do not很懂of genetic algorithm, is just the beginning stages of learning, hope and progress together

神 经 网 络 资 料-neural network data

人工神经网络matlab编程，BP网络实例 入境旅游人数的预测结果对于旅游管理部门和政府部门有着重要的参考意义,寻求科学合理的预测模型是保障预测结果准确可靠的关键。根据我国入境旅游人数的实际情况,建立由一个输入层、一个隐含层、一个输出层构成的三层BP 网络模型-ANN Matlab programming, BP examples tourist arrivals in the forecast results for the tourism management and government sectors have important reference value, search for a scientific and rational prediction model is to ensure accurate and reliable prediction of the key. According to China"s tourist arrivals in the actual situation, and establish an input layer, a hidden layer, an output layer consisting of a three-tier network model BP

一种基于BP网络的小波神经网络程序，用MATLAB编写的-BP network based on wavelet neural network procedures, prepared by using MATLAB

神经网络（模式识别模块）软件开发包!!!可以识别任何事物，适用于图像识别、语音识别、自动控制等诸多领域，具有简单、易学、开发周期短、识别率高等特点。-neural network (pattern recognition module) software development kit! ! ! Nothing can be identified and applied to image recognition, voice recognition, automatic control and many other areas, which is simple, easy to learn, short development cycle, features high recognition rate.