RANKING OF RANDOM BATCHES TO IDENTIFY PREDICTIVE FEATURES

摘要

Methods, media, and systems for selecting features that are predictive of a particular outcome from large sets of potentially-predictive features are disclosed. The feature-selection process involves generating random batches of features and ranking the batches according to how accurately a predictive model based on each batch of features performs. Predictive features are selected according to an aggregate rank of the batches in which they are included.

主权项

1. A method comprising:
receiving observed data representing a set of outcome values and, for each outcome value, a set of corresponding feature values for a set of potentially-predictive features; selecting a plurality of batches, wherein each batch is a randomly selected subset of features from the set of potentially-predictive features; generating, for each respective batch of the plurality of batches, an accuracy value for a predictive model based on the subset of features associated with the respective batch; ranking the plurality of batches according to the generated accuracy values for each batch; determining, for each respective feature in the set of potentially-predictive features, an aggregate rank for the subset of batches that include the respective feature; and selecting, as predictive features, features from the set of potentially-predictive features for which the determined aggregate rank satisfies a predetermined criterion.