Attribute Selection by Measuring Information on Reference Distributions

@inproceedings{Rosales2014AttributeSB,
  title={Attribute Selection by Measuring Information on Reference Distributions},
  author={R{\'o}mer Rosales},
  year={2014}
}
A great number of services, experiments, and decisions at Yahoo! require analyzing rich data sources. This data almost invariably holds a large number of attributes. In these scenarios, the efficient selection of relevant attributes is imperative for data analysis (e.g., modeling, prediction). When approaching new data analysis tasks, domain experts… CONTINUE READING