A Cognitive Bias Approach to Feature Selection and Weighting for Case-Based Learners

被引：0
|
作者：
Claire Cardie
机构：
[1] Cornell University,Department of Computer Science
来源：
Machine Learning | 2000年 / 41卷
关键词：
case-based learning; instance-based learning; feature set selection; feature weighting; natural language learning;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
Research in psychology, psycholinguistics, and cognitive science has discovered and examined numerous psychological constraints on human information processing. Short term memory limitations, a focus of attention bias, and a preference for the use of temporally recent information are three examples. This paper shows that psychological constraints such as these can be used effectively as domain-independent sources of bias to guide feature set selection and weighting for case-based learning algorithms.
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页码：85 / 116
页数：31
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