How to use Decision Tree Classification Matlab?

Question

I have data in form of rows and columns where rows represent a record and column represents its attributes. I also have the labels (classes) for those records.

I know about decision trees concept and I would like to use matlab for classification of unseen records using decision trees.

How can this be done? I followed this link but its not giving me correct output- Decision Tree in Matlab

Essentially I want to construct a decision tree based on training data and then predict the labels of my testing data using that tree. Can someone please give me a good and working example for this ?

score 1 · Accepted Answer · edited Nov 21 '13 at 13:35

1

I used following code to achieve it. And it is working correctly

function DecisionTreeClassifier(trainingFile, testingFile, labelsFile, outputFile)
training = csvread(trainingFile);
labels   = csvread(labelsFile);
testing  = csvread(testingFile);
tree = ClassificationTree.fit(training,labels)
prediction = predict(tree, testing)
csvwrite(outputFile, prediction)

edited Nov 21 '13 at 13:35

mamdouh alramadan

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answered Nov 18 '13 at 02:40

Kedar Joshi

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score 1 · Answer 2 · answered Nov 11 '17 at 13:47

1

ClassificationTree.fit will be removed in a future release. Use fitctree instead.

answered Nov 11 '17 at 13:47

Kadir GÜZEL

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How to use Decision Tree Classification Matlab?

2 Answers2