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...

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...

Firms have increasingly turned to rich digital media, such as videos and photos, to attract attention and boost awareness. Although extant research may help firms promote these media more effectively, the marketing process truly begins with creation of the media. Content creators may thus...