资源列表
arima
- 数据挖掘 人工智能 时间序列预测模型 matlab学习-Data Mining Artificial Intelligence Time series forecasting model matlab learning
IntelligentCar
- 智能控制系统最终大作业， 侧位停车，C语言仿真-Intelligent control system is the final big homework, side parking, C language simulation
pca-bp
- 在建模前先将数据利用PCA进行降维，将降维后的数据作为BP神经网络的输入因子，对数据进行拟合。-Before the first data modeling use PCA dimensionality reduction, the reduced dimensionality of the data as the input factor BP neural network, the data fitting.
FP-Growth
- 频繁模式挖掘算法FP-Growth，用于挖掘用户的频繁访问模式-Frequent pattern mining algorithm FP-Growth, for mining frequent user access patterns
prefixspan
- 序列模式挖掘算法PrefixSpan，主要用于挖掘频繁的访问序列-Sequential pattern mining algorithms PrefixSpan, mainly for mining frequent access sequences
dist
- 这是information retrival中一种search 工具的代码-This is the information retrival search tool source code.
parser-cPP
- 这是网络爬虫的实现算法，网络爬虫是搜索引擎的核心部件，Google,baidu都要自己的爬虫算法，一个好的爬虫技术，是实现功能的效率提高指点。-This is the implementation algorithm of web crawler, web crawler is the core component of search engine, Google, baidu will own the crawler algorithm, a good crawler technology,
PatternRecognition
- (1)Bayes分类 已知N=9， =3，n=2，C=3,问x= 应属于哪一类？ (2)聚类 使用c－均值聚类算法在IRIS数据上进行聚类分析 (3)鉴别分析 在ORL或Yale标准人脸数据库上完成模式识别任务。 用PCA与基于核的PCA（KPCA）方法完成人脸图像的重构与识别试验。-(1) Bayes classification Known N = 9, = 3, n = 2, C = 3, x = should ask which cat
DeepLearningTutorials
- deeplearning.net官网上的deep learning的教程，可以跟着网站上的内容一步一步的进行学习，达到快速入门的效果，是用python实现的-Deeplearning.net website deep learning tutorial, you can follow the content of the website step by step to learn, to achieve the effect of quick start, is made of python i
movieRecommendation
- 使用SlopeOne算法实现的电影推荐算法。-A movie recommendation algorithm SlopeOne algorithm implementation.
RFCM
- 利用粗糙模糊集聚类(RFCM)思想的聚类方法对UCI数据集中的Wine进行聚类分析。Wine数据集共包含13个属性，其中第一个是决策属性，剩下的是连续型的条件属性，一共包含178个对象。-Fuzzy clustering method using rough clustering (RFCM) thoughts on UCI Wine dataset cluster analysis. Wine data set contains a total of 13 properties, of whi
BP-network
- 训练样本对BP网络训练，可输入测试样本，设置目标期望输出-Training samples for BP network training, enter the test samples, set the desired output target