资源列表
K-means
- 本程序是用python写的一个K均值算法，通过该算法可以学习一python实现算法的流程，以及学习该算法的使用。-The program is written in python a K-means algorithm, the algorithm can learn a python algorithm implementation processes, and learning to use the algorithm.
DecisionTree
- 本程序是利用python写的一个决策树算法，通过该例子可以实现简单的决策树处理，也可以学习决策树算法的基本思想。-This procedure is to use python to write a decision tree algorithm, this example can be achieved by a simple decision tree processing, you can also learn the basic idea of the decision tree alg
Bayes
- 本程序是使用的Python写的一个Bayes分类器，通过这个程序可以大致掌握Bayes的原理。-This procedure is used to write a Python Bayes classifier, through this program can be broadly master the principles of Bayes.
CUSUM
- CUSUM算法程序,使用CUSUM方法检测残差的跳变.-CUSUM algorithm, the use of CUSUM method for detecting residual transition.
KNN
- KNN近邻算法分类程序,包含训练数据和测试数据.-KNN classification procedures, including training and testing data.
08ClusAdvanced-1
- 综合介绍聚类分析的方法，从常用方法到高级方法-Overview cluster analysis, the common method to advanced methods
R_Q2
- 先进行逐步回归，后对其残差进行sarima预测-First stepwise regression, after its prediction residuals sarima
perceptron
- 使用matlab编写的感知机算法，并提供测试数据集，方便测试-Using matlab prepared Perceptron algorithms and provide test data sets, to facilitate testing
kNN
- 使用python编写kNN算法，包括生成数据集，简单分类器，文本转换等简单算法。-Using python write kNN algorithms, including generating a data set, a simple classification, text conversion simple algorithm.
GSP
- GSP是基于apriori思想的高效序列模式挖掘算法，不用二次遍历所有序列集。-GSP is based on highly efficient sequential pattern mining algorithm apriori thought, do not traverse all secondary sequence set.
Apriori
- Apriori算法是一种最有影响的挖掘布尔关联规则频繁项集的算法。其核心是基于两阶段频集思想的递推算法。- Apriori algorithm is one of the most influential mining Boolean association rules frequent itemsets algorithm. Its core is based on a two-stage frequency set recursive algorithm thought.
Apriori
- 带测试的 apriori 做了优化修改,测试文件和源代码，以及整个工程都在里面-apriori test with optimized modification, testing, documentation and source code, as well as the whole project are inside