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- ArticleAugust 2003
Experimental design for solicitation campaigns
KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data miningAugust 2003, Pages 717–722https://doi.org/10.1145/956750.956846Data mining techniques are routinely used by fundraisers to select those prospects from a large pool of candidates who are most likely to make a financial contribution. These techniques often rely on statistical models based on trial performance data. ...
- ArticleAugust 2003
Experiments with random projections for machine learning
KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data miningAugust 2003, Pages 517–522https://doi.org/10.1145/956750.956812Dimensionality reduction via Random Projections has attracted considerable attention in recent years. The approach has interesting theoretical underpinnings and offers computational advantages. In this paper we report a number of experiments to evaluate ...
- ArticleAugust 2003
Assessment and pruning of hierarchical model based clustering
KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data miningAugust 2003, Pages 197–205https://doi.org/10.1145/956750.956775The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mixture of Gaussians, and to estimate the parameters of the component ...
- ArticleAugust 2003
Information-theoretic co-clustering
KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data miningAugust 2003, Pages 89–98https://doi.org/10.1145/956750.956764Two-dimensional contingency or co-occurrence tables arise frequently in important applications such as text, web-log and market-basket data analysis. A basic problem in contingency table analysis is co-clustering: simultaneous clustering of the rows and ...