classification using decision tree

I have A=[0.0218 -0.0324 -0.0107 -0.0324 0.0001 -0.0107 -0.0107 -0.0324 -0.0216 0.0001 -0.0162 -0.0324 0.0055 -0.0541 0.0272 -0.0324

0.1355 0.0001 0.0542 0.0651 0.0651 0.0272 0.0542 0.0163 -0.0053 -0.0053].How can I do classification using decision tree using these points my dataset is attached here.The A is the set extracted from Train set.

Answer 1

[Jyothis Gireesh]

I am assuming that there may be some problem with the file names as the file ‘ECGFiveDays_TRAIN.xlsx’ contains only 23 records and ‘ECGFiveDays_TEST.xlsx’ contains 861 records. It may not be optimal to fit the decision tree using just 23 records and then evaluate the resulting model on a bigger dataset.

So, for the following code I have taken the liberty of using the bigger dataset as the training data. Please make use of the following code snippet to perform the classification using decision trees.

clear; 
trainData = xlsread('ECGFiveDays_TEST.xlsx'); 
testData = xlsread('ECGFiveDays_TRAIN.xlsx'); 
tree = fitctree(trainData(:,2:end),trainData(:,1));        %Fit the dataset using decision tree 
predictLabels = predict(tree,testData(:,2:end));            %Evaluate on test dataset 
trueLabels = testData(:,1); 
testAccuracy = sum(predictLabels == trueLabels)/length(trueLabels);

Please go through the following documentation link on “fitctree()” if you need any further clarifications on the same

https://www.mathworks.com/help/stats/fitctree.html

[Silpa K]

Thank you sir.