Machine Learning: Decision Tree Using Weka

Decision Tree

A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm.

Decision Tree Using Weka

We are going to use Weka. Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, classification, regression, clustering, association rules, and visualization. It is also well-suited for developing new machine learning schemes.
You can download Weka from here.
Open weka.jar and after download, it will look like,
Click on 'Explorer'. A new window will appear. First, browse the file and load the dataset you want to make a decision tree.
Navigate to classify. Select File, select Tree type and then check the Load Training Data. After then click Start,
Get gif.

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