In this code, we have done a comparison between four classifier (KNN decision tree RBF wighted KNN ).
Three datasets are selected for input :
glass.mat , Heart.mat , WDBC.mat
10-fold cross validation are used for testing final performance of each classifier.
Output of each MATLAB code is similar to the following line :
Method | Mean | STD | MCC | F1 | specificity | sensivity | Time
Tree | 0.98117 | 0.033096 | 0.95908 | 0.97238 | 0.97905 | 0.98571 | 0.39398
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