搜索资源列表
matlab
- 用于SVM实现不同算法对不同数据集性能测试的MATLAB代码，包括离线，在线算法。-SVM implement different algorithms for different data sets to performance testing MATLAB code, including offline and online algorithms.
scaleForSVM
- 用SVM进行分类时，需要对原数据进行归一化处理。-When using SVM classification, the need for raw data normalized.
SVM-timeseries
- 基于SVM的时序序列预测，用python实现，内附测试数据，方便可用。-SVM prediction based on a timing sequence with python to achieve, enclosing the test data to facilitate available.
SVM-KM
- 支持向量机与核学习工具箱，用于数据挖掘中核方法开发的必备工具，如支持向量机、极限学习机等。-Support vector machine (SVM) and nuclear learning toolkit for nuclear method development of necessary tools in data mining, such as support vector machine (SVM), extreme learning machine, etc.
data-mining
- 常用的一些数据挖掘算法，包括Apriori,SVM,神经网络，遗传算法，K-means。-some commonly used data-mining algorithms,including Apriori,SVM,Neural Network，Genetic algorithm，K-means
SVM-and-NB
- 支持向量机与朴素贝叶斯算法，对数据进行分类后深度了解数据的结构-Support vector machine and naive Bayes algorithm.Classifying the data and understanding the structure of the data in depth
py脚本
- svm支持向量机，包括训练数据，训练代码和测试代码(SVM support vector machines, welcome to download, including the data set)
KNN，SVM，决策树，朴素贝叶斯
- 用python的sklearn包分类 简单的对数据进行分类(Sort with Python's sklearn package Simple classification of data)
MachineLearningLab-master
- 使用2种分类方法随机森林、SVM对数据进行分类(Classification of data using random forests and SVM)