Value of information lattice: exploiting probabilistic independence for effective feature subset acquisition

TitleValue of information lattice: exploiting probabilistic independence for effective feature subset acquisition
Publication TypeJournal Articles
Year of Publication2011
AuthorsBilgic M, Getoor L
JournalJournal of Artificial Intelligence Research
Volume41
Issue2
Pagination69 - 95
Date Published2011/05//
ISBN Number1076-9757
Abstract

We address the cost-sensitive feature acquisition problem, where misclassifying an instance is costly but the expected misclassification cost can be reduced by acquiring the values of the missing features. Because acquiring the features is costly as well, the objective is to acquire the right set of features so that the sum of the feature acquisition cost and misclassification cost is minimized. We describe the Value of Information Lattice (VOILA), an optimal and eficient feature subset acquisition framework. Unlike the common practice, which is to acquire features greedily, VOILA can reason with subsets of features. VOILA eficiently searches the space of possible feature subsets by discovering and exploiting conditional independence properties between the features and it reuses probabilistic inference computations to further speed up the process. Through empirical evaluation on five medical datasets, we show that the greedy strategy is often reluctant to acquire features, as it cannot forecast the benefit of acquiring multiple features in combination.

URLhttp://dl.acm.org/citation.cfm?id=2051237.2051240