Searching for Interacting Features
Zheng Zhao, Huan Liu
Feature interaction presents a challenge to feature selection for classification. A feature by itself may have little correlation with the target concept, but when it is combined with some other features, they can be strongly correlated with the target concept. Unintentional removal of these features can result in poor classification performance. Handling feature interaction can be computationally intractable. Recognizing the presence of feature interaction, we propose to efficiently handle feature interaction to achieve efficient feature selection and present extensive experimental results of evaluation.