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Indexing Cost Sensitive Prediction
[article]
2014
arXiv
pre-print
Predictive models are often used for real-time decision making. However, typical machine learning techniques ignore feature evaluation cost, and focus solely on the accuracy of the machine learning models obtained utilizing all the features available. We develop algorithms and indexes to support cost-sensitive prediction, i.e., making decisions using machine learning models taking feature evaluation cost into account. Given an item and a online computation cost (i.e., time) budget, we present
arXiv:1408.4072v1
fatcat:oorh5l2qknekbhkxa7um3gkjn4