informaatioarvoksi
Informaatioarvoksi is a concept used in information theory, data science and statistics to quantify the value of information provided by a signal, feature, or message for reducing uncertainty in a decision problem. It captures how much expected reduction in uncertainty a given piece of information yields relative to a prior state, and it is often used to compare information sources or predictors in modelling tasks.
Historically, informaatioarvoksi draws on Shannon's information theory and Bayesian decision theory. In practice, it is frequently
Measurement: a widely used definition in data mining is IV = sum_i ( (p1_i - p0_i) × ln(p1_i/p0_i) ), where
Applications and limitations: IV is used to rank and select features for predictive models, to gauge the
See also: entropy, mutual information, Kullback-Leibler divergence, weight of evidence, information theory.