Optimization of control parameters for genetic algorithms
IEEE Transactions on Systems, Man and Cybernetics
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The Use of Background Knowledge in Decision Tree Induction
Machine Learning
C4.5: programs for machine learning
C4.5: programs for machine learning
An Approximate Nonmyopic Computation for Value of Information
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning cost-sensitive active classifiers
Artificial Intelligence
Machine Learning
Learning diagnostic policies from examples by systematic search
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Test-Cost Sensitive Classification on Data with Missing Values
IEEE Transactions on Knowledge and Data Engineering
Enhancing Automated Test Selection in Probabilistic Networks
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Active Feature-Value Acquisition
Management Science
VOILA: efficient feature-value acquisition for classification
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Journal of Artificial Intelligence Research
Myopic value of information in influence diagrams
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
Determining the value of information for collaborative multi-agent planning
Autonomous Agents and Multi-Agent Systems
Light at the end of the tunnel: a Monte Carlo approach to computing value of information
Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Towards anytime active learning: interrupting experts to reduce annotation costs
Proceedings of the ACM SIGKDD Workshop on Interactive Data Exploration and Analytics
An exact algorithm for computing the same-decision probability
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Look versus leap: computing value of information with high-dimensional streaming evidence
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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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.