Question

2. Decision Trees (5 pts) Consider the training dataset given below. In this dataset, X1, X2, and X3 are the input attributes and Y is the class variable. "+ve" and "-ve" are the two outcome classes, similar to "Yes" and "no". Example# X1 X2 X3 Y E1 0 0 0 +ve E2 0 0 1 -ve E3 0 1 0 -ve E4 0 1 1 +ve E5 1 0 0 -ve Which attribute has the highest information gain, i.e., reduction in Gini Index? Justify your answer. Use Gini Index ($1 - p_1^2 - p_2^2$) as measurement criteria

Name: 2 decision trees 5 pts consider the training dataset given below in this dataset x1 x2 and x3 are the input attributes and y is the class variable ve and ve are the two outcome classes simil 76565
Uploaded: 2022-01-17T13:06:33-08:00
Duration: 4 min 34 s
Channel: Ameer Said
Description: 2 decision trees 5 pts consider the training dataset given below in this dataset x1 x2 and x3 are the input attributes and y is the class variable ve and ve are the two outcome classes simil 76565

          2. Decision Trees (5 pts)
Consider the training dataset given below. In this dataset, X1, X2, and X3 are the input attributes and Y is the class variable. "+ve" and "-ve" are the two outcome classes, similar to "Yes" and "no".

Example#	X1	X2	X3	Y
E1	0	0	0	+ve
E2	0	0	1	-ve
E3	0	1	0	-ve
E4	0	1	1	+ve
E5	1	0	0	-ve

Which attribute has the highest information gain, i.e., reduction in Gini Index? Justify your answer. Use Gini Index ($1 - p_1^2 - p_2^2$) as measurement criteria

2 decision trees 5 pts consider the training dataset given below in this dataset x1 x2 and x3 are the input attributes and y is the class variable ve and ve are the two outcome classes simil 76565

Added by Karina W.

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