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RandomForest
- 机器学习随机森林源码。改变决策树的深度对比分类结果。对鸢尾花数据进行决策树分析-random forest
程序
- Fisher判别适合于两类的判别分析。本文采用的鸢尾花数据库中鸢尾花类别有三类，所以先采用Fisher判别对数据进行二分类判别分析，然后采用一对一进行多分类。(Fisher discriminant analysis is suitable for two kinds of discriminant analysis. There are three categories of iris in the iris database in
fisher判别分析
- 利用fisher判别分析对于鸢尾花数据集进行分类(Fisher discriminant analysis was used to classify iris data sets)
Iris-Dataset-Analysis-master
- 用决策树-回归分析模型来分析鸢尾花数据，训练后最终可以得到模型的准确率(Using decision tree-regression analysis model to analyze iris data, the accuracy of the model can be obtained after training.)
鸢尾花 数据的处理
- MATLAB 利用Fisher分析和核Fisher分析对鸢尾花数据集进行分类，可以发现Kfisher 可以较好地对非线性数据的分类(MATLAB USES Fisher analysis and core Fisher analysis to classify the iris data set, and it can be found that Kfisher can classify the nonlinear data well)