资源列表
AdaBoost
- 加强树算法的一个实例,最后取得了很好的分类结果,便于推广,分类器的代码可以根据实际进行更改。-Strengthen an instance tree algorithm, finally achieved good classification results, easy to promote, classification code can actually make changes.
tssvm--bfgs
- 对三次样条函数的模型利用BFGS算法进行优化求解-Cubic spline function model using BFGS algorithm optimization solution
ctssvm--bfgs
- 对无约束的优化模型利用BFGS算法进行求解-For unconstrained optimization model uses BFGS algorithm to solve
linear_CTSSVM
- 基于分段函数的支持向量分类机,使用BFGS算法进行求解-Piecewise-based support vector machine, using BFGS algorithm to solve
LOW-density-seperation
- 使用LDS(low density seperation)method 寻找最优分离面,然后对数据进行分类-Use LDS (low density seperation) method to find the optimal separation surface, and then classify the data
recommender-
- Collaborative Filtering,基于Collaborative Filtering,建立主动为用户推荐商品的推荐系统。实现参考协同过滤算法或它的优化,实现并改进算法,计算出每个客户对未购买的商品的兴趣度,并向客户主动推荐他最感兴趣的N个商品。实验数据可以从MovieLens.com下载。要求使用至少10,000不同用户的数据,至少1000个不同的movie。-Collaborative Filtering,Based Collaborative Filtering, the in
crawler
- python 爬虫爬取http://accent.gmu.edu/网站上的音频文件-Using python crawler to scape data the George Mason University Department of English Speech Accent Archive.
delete-character
- 任意输入字符串,把相同的字符清楚掉,剩下的字符按原先的排序组合在一起-Any input string, the same character clear out the rest of the characters are combined together in the original sorting
data-mining_GRI
- GRI关联数据挖掘. GRI是关联规则的一种算法。很有用的。-GRI association data mining
NaiveBayes
- 贝叶斯分类器,机器学习十大经典算法之一,基本的实现-Naive Bayes
BinningandFeatSelection_GeneData
- Code to discretize and gene features. Works with numeric features with classes labeled as positive and negative-Code to discretize and gene features. Works with numeric features with classes labeled as positive and negative
prefixspan
- 经典序列模式挖掘算法prefixspan的python实现-Classic sequence pattern mining algorithm prefixspan