@inproceedings{473c27fef45142c18eb9a87b35992516,
title = "Evaluation of prediction models for marketing campaigns",
abstract = "We consider prediction-model evaluation in the context of marketing-campaign planning. In order to evaluate and compare models with specific campaign objectives in mind, we need to concentrate our attention on the appropriate evaluation-criteria. These should portray the model's ability to score accurately and to identify the relevant target population. In this paper we discuss some applicable model-evaluation and selection criteria, their relevance for campaign planning, their robustness under changing population distributions, and their employment when constructing confidence intervals. We illustrate our results with a case study based on our experience from several projects.",
keywords = "Confidence Intervals, Marketing Campaigns, Model Evaluation, Performance Measures",
author = "Saharon Rosset and Einat Neumann and Uri Eick and Nurit Vatnik and Izhak Idan",
year = "2001",
doi = "10.1145/502512.502581",
language = "אנגלית",
isbn = "158113391X",
series = "Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",
publisher = "Association for Computing Machinery (ACM)",
pages = "456--461",
editor = "F. Provost and R. Srikant and M. Schkolnick and D. Lee",
booktitle = "Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",
address = "ארצות הברית",
note = "Proceedings of the Seventh ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2001) ; Conference date: 26-08-2001 Through 29-08-2001",
}