Learning binary relations and total orders
SIAM Journal on Computing
The Power of Self-Directed Learning
Machine Learning
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Being taught can be faster than asking questions
COLT '95 Proceedings of the eighth annual conference on Computational learning theory
Online learning versus offline learning
EuroCOLT '95 Proceedings of the Second European Conference on Computational Learning Theory
Active learning: theory and applications
Active learning: theory and applications
Mining Customer Value: From Association Rules to Direct Marketing
Data Mining and Knowledge Discovery
ICML '06 Proceedings of the 23rd international conference on Machine learning
Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner
Introduction to Information Retrieval
Introduction to Information Retrieval
Active learning with statistical models
Journal of Artificial Intelligence Research
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
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Direct marketing is one of the most common and crucial business intelligence tasks. In direct marketing, the goal of an agent is to mine the right customers to market certain products, with the goal of making fewest mistakes. This data-mining problem, though similar to active learning in terms of allowing the agent to select customers actively, is, in fact, opposite to active learning. As far as we know, no previous data mining algorithms can solve this problem well. In this paper, we propose a simple yet effective algorithm called Most-Certain Learning (MCL) to handle this type of problems. The experiments show that our data-mining algorithms can solve various direct marketing problems effectively.