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...

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 even prohibitively expensive. Active feature-value acquisition (AFA) elects...

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...

It can be expensive to acquire the data required for businesses toemploy data-driven predictive modeling, for example to model consumerpreferences to optimize targeting. Prior research has introduced“active learning” policies for identifying data that areparticularly useful for model...

In many cost-sensitive environments class probability estimates are used by decisionmakers to evaluate the expected utility from a set of alternatives. Supervisedlearning can be used to build class probability estimates; however, it often is verycostly to obtain training data with class labels....

For many supervised learning tasks, the cost of acquiringtraining data is dominated by the cost of class labeling.In this work, we explore active learning forclass probability estimation (CPE). Active learning acquiresdata incrementally, using the model learned sofar to help identify especially...

This paper addresses focused information acquisition for predictive data mining. Asbusinesses strive to cater to the preferences of individual consumers, they often employpredictive models to customize marketing efforts. Building accurate models requiresinformation about consumer preferences...