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Comparison between KNN decision tree RBF wighted KNN

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Description

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

 

output code of decision tree classifier MATLAB

 

 

 

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