What is a Decision Tree A Decision Tree is a type of supervising algorithm which indicates that in the training set you know the input variable ( features ) and their corresponding target. Decision Tree can operate as both classifiers or regressors. In this method, we split the dataset into two or more uniform sets based on the most significant splitter/differentiator in the dataset features. Example:- Let’s say we have a sample of 50 studen t s with three variables Gender (Boy/ Girl), Class( X/ XI) and Height (5 to 6 ft). 20 out of these 50 play cricket in rest time. Suppose you want to find on unknown dataset which contains all the features(Gender, class, height) that he/she will play or not in rest time. This is where decision tree supports, it will separate the students based on all values of three variable and identify the variable, which creates the best uniform sets of students like below: Terms you should know Root Node: It describes the complete dataset and this ad...
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