Systems and methods for selecting features for classification

A computer-implemented method for selecting features for classification may include (1) generating a matrix X, a column vector Y, and a matrix Z from a training dataset that includes a plurality of samples with a plurality of features, (2) generating an augmented matrix from the matrix X, the column...

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Bibliographic Details
Main Authors Vasiloglou, Nikolaos, Parikh, Jugal, Gardner, Andrew
Format Patent
LanguageEnglish
Published 30.07.2019
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Summary:A computer-implemented method for selecting features for classification may include (1) generating a matrix X, a column vector Y, and a matrix Z from a training dataset that includes a plurality of samples with a plurality of features, (2) generating an augmented matrix from the matrix X, the column vector Y, and the matrix Z, (3) identifying one or more most-relevant features from the plurality of features by iteratively applying a sweep operation to the augmented matrix, and (4) training a classification model using the most-relevant features from the plurality of features rather than all of the plurality of features. Various other methods, systems, and computer-readable media may have similar features.
Bibliography:Application Number: US201615087743