phdcomputer Eng asked . 2022-04-02

How to apply majority voting for classification ensemble in Matlab?

I have five classifiers SVM, random forest, naive Bayes, decision tree, KNN,I attached my Matlab code. I want to combine the results of these five classifiers on a dataset by using majority voting method and I want to consider all these classifiers have the same weight. because the number of the tests is calculated 5 so the output of each classifier is 5 labels(class labels in this example is 1 or 2). I'll be gratefull to have your opinions 

clear all
close all
clc
load data.mat;
data=data;
[n,m]=size(data);
rows=(1:n);
test_count=floor((1/6)*n);
sum_ens=0;sum_result=0;
test_rows=randsample(rows,test_count);
train_rows=setdiff(rows,test_rows);
test=data(test_rows,:);
train=data(train_rows,:);
xtest=test(:,1:m-1);
ytest=test(:,m);
xtrain=train(:,1:m-1);
ytrain=train(:,m);

%-----------svm------------------
svm=svm1(xtest,xtrain,ytrain);

%-------------random forest---------------
rforest=randomforest(xtest,xtrain,ytrain);

%-------------decision tree---------------
DT=DTree(xtest,xtrain,ytrain);

%---------------bayesian---------------------
NBModel = NaiveBayes.fit(xtrain,ytrain, 'Distribution', 'kernel');
Pred = NBModel.predict(xtest);
dt=Pred;

%--------------KNN----------------
knnModel=fitcknn(xtrain,ytrain,'NumNeighbors',4);
     pred=knnModel.predict(xtest);
     sk=pred;

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