Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner
3rd Edition
ISBN: 9781118729274
Author: Galit Shmueli, Peter C. Bruce, Nitin R. Patel
Publisher: WILEY
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Chapter 5, Problem 1P
Explanation of Solution
Given: A routine is applied with the help of data mining to the transaction dataset. The transaction dataset is categorized into fraudulent and non-fraudulent that has 88 records (30 correctly) and 952 records (920 correctly), respectively.
To find:Â The classification matrix and determine the error rate.
Solution:
In the given context, classification matrix provides the most accurate measure from the dataset.
The number of C0,1 classified cases correctly is n(0,0) = 30.
The number of C0,1 classified cases incorrectly as C1,0 is n(0,1) = 58.
The number of C1,0 classified cases incorrectly as C0,1 is n(1,0) = 32.
The number of C1,0 classified cases correctly is n(1,1) = 920.
The following is the classification matrix:
By analyzing the classification matrix, the values of both fraudulent and non-fraudulent are as follows:
The actual rate of fraudulent is n(0,1) = 58.
The actual rate of non-fraudulent is n(1,0) = 32.
Total number of records present in the dataset is n = 30 + 58 + 32 + 920 = 1040.
Evaluate the rate of error present in the dataset by using the formula of error rate.
Hence, the error rate is 8.65%.
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Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner
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