The following table consists of training data from product sales. For a given row entry, count...

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The following table consists of training data from product sales. For a given row entry, count represents the number of data tuples having the values for attributes given in that row. Profession Gender Engineer M Lawyer M Engineer F F Lawyer Lawyer Lawyer M F Income H H H H L L count 5 20 20 5 25 25 Bought Smartwatch Yes No Yes No Yes No Build a Decision Tree for the above training data using Gini Index as attribute selection measure. Activate Windows The following table consists of training data from product sales. For a given row entry, count represents the number of data tuples having the values for attributes given in that row. Profession Gender Engineer M Lawyer M Engineer F F Lawyer Lawyer Lawyer M F Income H H H H L L count 5 20 20 5 25 25 Bought Smartwatch Yes No Yes No Yes No Build a Decision Tree for the above training data using Gini Index as attribute selection measure. Activate Windows

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Solutions Step 1 To build a decision tree using Gini index we need to first calculate the Gini index for each attribute Gini Index Formula GiniD 1 sumcountccountD2 where D is the dataset c is the clas... View the full answer