Feature Selection based on the Local Lift Dependence Scale.

ABSTRACT: This paper uses a classical approach to feature selection: minimization of a cost function applied on estimated joint distributions. However, in this new formulation, the optimization search space is extended. The original search space is the Boolean lattice of features sets (BLFS), while the extended one is a collection of Boolean lattices of ordered pairs (CBLOP), that is (features, associated value), indexed by the elements of the BLFS. In this approach, we may not only select the features that are most related to a variable Y, but also select the values of the features that most influence the variable or that are most prone to have a specific value of Y. A local formulation of Shannon's mutual information, which generalizes Shannon's original definition, is applied on a CBLOP to genera

SUBMITTER: Marcondes D 

PROVIDER: S-EPMC7512664 | biostudies-literature | 2018 Jan

REPOSITORIES: biostudies-literature