COMPUTER SCIENCE AND ENGINEERING
MACHINE LEARNING
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Gini
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Entropy
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Information Gain
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Random
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Detailed explanation-1: -Decision Trees (DTs) are a non-parametric supervised learning method used for classification and regression. The goal is to create a model that predicts the value of a target variable by learning simple decision rules inferred from the data features. A tree can be seen as a piecewise constant approximation.
Detailed explanation-2: -Which one is implemented in scikit-learn? ID3 (Iterative Dichotomiser 3) was developed in 1986 by Ross Quinlan. The algorithm creates a multiway tree, finding for each node (i.e. in a greedy manner) the categorical feature that will yield the largest information gain for categorical targets.
Detailed explanation-3: -criterion : This parameter determines how the impurity of a split will be measured. The default value is “gini” but you can also use “entropy” as a metric for impurity. splitter: This is how the decision tree searches the features for a split. The default value is set to “best”.