Binary classification through SVM/Decision tree ( Mat. Code)
The data set is partitioned for training/testing. Scatter plot/confusion matrix/ROC curve is plotted through MATLAB code.
Here, The data set is partioned into (30/70) ratio for testing and training. The detailed procedure is listed below.
Reading training data set
Randomise training set
Creating testing set (partioning in 30/70 ratio).
Model development (either SVM/Decision tree)
Plotting Scatter plot
Plotting confusion matrix
Prediction of data
Saving predicted data in excel set.
See the Zip file for further information.
引用格式
Samarjeet Kumar (2026). Binary classification through SVM/Decision tree ( Mat. Code) (https://ww2.mathworks.cn/matlabcentral/fileexchange/130374-binary-classification-through-svm-decision-tree-mat-code), MATLAB Central File Exchange. 检索时间: .
| 版本 | 已发布 | 发行说明 | Action |
|---|---|---|---|
| 1.0.0 |
