Reference no: EM132332264
Assignment -
Answer the following questions. Move all graphs, charts, and tables to the single document. Use APA style references and citations if needed. These questions are from Chapter 5 of Shmueli, Bruce, and Patel.
1. A data mining procedure has classified 88 records as fraudulent (30 correctly so) and 952 as non-fraudulent (920 correctly so). Build the classification matrix and calculate the error rate. Explain how the error rate is calculated. Explain in your own words how each cell in the confusion matrix is calculated.
2. Suppose there is an adjustable cutoff value used to alter the proportion of records classified as fraudulent. Describe in your own words how moving the cutoff up or down would affect:
a. The classification error rate for records that are truly fraudulent.
b. The classification error rate for records that are truly non-fraudulent.
Be sure to write in complete, well-considered sentences and avoid ambiguity in your answers.
3. A large number of insurance records are to be examined to develop a model for predicting fraudulent claims. Of the claims in the historical database, 1 percent were fraudulent. A sample is used to develop a model, and oversampling is used to provide a balanced sample in light of the low response rate. When applied to this sample, (800 records), the model correctly classifies 310 frauds and 270 non-frauds. It missed 90 frauds and classified 130 records incorrectly as frauds when they were not.
a. Make the classification matrix for the sample.
b. Find the adjusted misclassification rate (adjusting for oversampling.)
c. What percentage of new records would you expect to be classified as fraudulent?
References - Shmueli, G., Bruce, P., Patel, N., (2016). Data Mining for Business Analytics, Concepts, Techniques, and Applications with XLMiner. Hoboken, NJ: John Wiley & Sons, Inc.
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