Abstract. In many cost-sensitive environments class probabilityestimates are used by decision makers to evaluate the expected utilityfrom a set of alternatives. Supervised learning can be used to buildclass probability estimates; however, it often is very costly to obtaintraining data with class...

In many classification tasks training data have missing feature valuesthat can be acquired at a cost. For building accurate predictive models,acquiring all missing values is often prohibitively expensive orunnecessary, while acquiring a random subset of feature values may notbe most effective....

Most induction algorithms for building predictive models take as input training data in the form of feature vectors. Acquiring the values of features may be costly, and simply acquiring all values may be wasteful or prohibitively expensive. Active feature-value acquisition (AFA) selects features...