Consider the training set given below, where X, X2, X3 and X4 are attributes and Y...

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Consider the training set given below, where X₁, X2, X3 and X4 are attributes and Y is the target value. Y X₁ X₂ X3 X4 +1 0 1 0 1 +1 1 1 0 +1 0 +1 1 0 1 -1 -1 -1 -1 1 0 1 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 1 0 1 1 0 0 1 0 0 1 1 a. (Group work) Implement the ID3 algorithm and show what tree results. Please make sure that you are implementing ID3 and are not using some decision tree algorithm/package. Make sure your program, at each split point, prints out the entropy at that time and the information gain of each attribute at that time. b. (Individual work) Design by hand a tree with 4 leaf nodes, 3 internal nodes and depth bounded by two which is consistent with this training data. Consider the training set given below, where X₁, X2, X3 and X4 are attributes and Y is the target value. Y X₁ X₂ X3 X4 +1 0 1 0 1 +1 1 1 0 +1 0 +1 1 0 1 -1 -1 -1 -1 1 0 1 0 0 0 1 0 0 1 0 1 0 0 0 0 0 0 1 0 1 1 0 0 1 0 0 1 1 a. (Group work) Implement the ID3 algorithm and show what tree results. Please make sure that you are implementing ID3 and are not using some decision tree algorithm/package. Make sure your program, at each split point, prints out the entropy at that time and the information gain of each attribute at that time. b. (Individual work) Design by hand a tree with 4 leaf nodes, 3 internal nodes and depth bounded by two which is consistent with this training data.

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a Implementation of ID3 Algorithm Calculate the Y entropy of the target variable for the entire data set Calculate the information to be obtained for each factor X1 X2 X3 and X4 Identify the element w... View the full answer