The marketing department of a riding mower manufacturer wants to understand who are more likely to buy their riding mowers. A group of data analysts is building a classification tree to classify its customers into two classes: nonowners (class 0) and owners (class 1) of riding mowers. Each customer is described by two attributes: income and lot size. The data analysts have agreed to split a set of training records (denoted by A) using customer's lot size. Two subsets of records (denoted by A1 and A2 respectively) are produced after splitting A. The number of nonowners and owners in A, A1, and A2 are given below. A 56 104 Number of Nonowners Number of Owners A1 49 44 A2 7 60
The marketing department of a riding mower manufacturer wants to understand who are more likely to buy their riding mowers. A group of data analysts is building a classification tree to classify its customers into two classes: nonowners (class 0) and owners (class 1) of riding mowers. Each customer is described by two attributes: income and lot size. The data analysts have agreed to split a set of training records (denoted by A) using customer's lot size. Two subsets of records (denoted by A1 and A2 respectively) are produced after splitting A. The number of nonowners and owners in A, A1, and A2 are given below. A 56 104 Number of Nonowners Number of Owners A1 49 44 A2 7 60
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The combined entropy of A1 and A2 is .
The reduction in entropy if training records are split using customer’s lot size is .
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