| Publisher | SAS Institute | ||
|---|---|---|---|
| Format | 159.8KB PDF | Date added | 14 May 2007 |
| Topics | Data Mining - Analysis, Knowledge and Data Management | ||
| Downloads | 13 | ||
The market department of a financial firm keeps records on customers, including demographic information and their type of accounts. The firm is launching a new product and wishes to determine who are the best prospects among the existing customers for this new product. People are asked to provide a list of 1000 best prospects. Regression, decision tree and neural network models are built to use for scoring the prospective customers. A confusion matrix is then used to determine what the cut-off point for the scores for customers should be used to determine who qualifies as a good target. The models are compared by assessing model performance and validating the model to new data.
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