RANDOM FOREST CLASSIFICATION-MATLAB (with Complete Code & Data)

Check this link to know more about fitensemble:
https://in.mathworks.com/help/stats/f...
Prerequisite:
   • Random Forest Classifier and Regresso...  

Dataset:
https://github.com/SatadruMukherjee/D...

Decision Tree Classifier Code:

clc
clear all
close all
warning off
data=readtable('study_data.csv');
k=["High","Low"];
l=[1,0];
g=data.knowledge_level;
number=zeros(length(g),1);
for i=1:length(k)
rs=ismember(g,k(i));
number(rs)=l(i);
end
data.category_encoded=number;
data.knowledge_level=[];
cv = cvpartition(size(data,1),'HoldOut',0.3);
idx = cv.test;
dataTrain=data(~idx,:);
dataTest=data(idx,:);
testing=dataTest(1:end,1:end-1);
model=fitctree(dataTrain,'category_encoded');
prediction=predict(model,testing);
ms=(sum(prediction==table2array(dataTest(:,end)))/size(dataTest,1))*100
e=min(data.x___repetition_time):0.01:max(data.x___repetition_time);
f=min(data.study_time):0.01:max(data.study_time);
[x1 x2]=meshgrid(e,f);
x=[x1(:) x2(:)];
ms=predict(model,x);
gscatter(x1(:),x2(:),ms,'cy');
hold on;
gscatter(dataTrain.x___repetition_time,dataTrain.study_time,dataTrain.category_encoded,'rg','.',30);


Random Forest Code:

clc
clear all
close all
warning off
data=readtable('study_data.csv');
k=["High","Low"];
l=[1,0];
g=data.knowledge_level;
number=zeros(length(g),1);
for i=1:length(k)
rs=ismember(g,k(i));
number(rs)=l(i);
end
data.category_encoded=number;
data.knowledge_level=[];
cv = cvpartition(size(data,1),'HoldOut',0.3);
idx = cv.test;
dataTrain=data(~idx,:);
dataTest=data(idx,:);
testing=dataTest(1:end,1:end-1);
model=fitensemble(dataTrain,'category_encoded','Bag',100,'Tree','Type','classification');
prediction=predict(model,testing);
ms=(sum(prediction==table2array(dataTest(:,end)))/size(dataTest,1))*100
e=min(data.x___repetition_time):0.01:max(data.x___repetition_time);
f=min(data.study_time):0.01:max(data.study_time);
[x1 x2]=meshgrid(e,f);
x=[x1(:) x2(:)];
ms=predict(model,x);
gscatter(x1(:),x2(:),ms,'cy');
hold on;
gscatter(dataTrain.x___repetition_time,dataTrain.study_time,dataTrain.category_encoded,'rg','.',30);


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