HPL-2007-164(R.1) Quantifying Counts, Costs, and Trends Accurately via Machine Learning - Forman, George
Keyword(s): supervised machine learning, classification, prevalence estimation, class distribution estimation, cost quantification, quantification research methodology, minimizing training effort, detecting and tracking trends, concept drift, class imbalance, text mining
Abstract: In many business and science applications, it is important to track trends over historical data, for example, measuring the monthly prevalence of influenza incidents at a hospital. In situations where a machine learning classifier is needed to identify the relevant incidents from among all cases in ...
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