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.