Mixture of Deep Neural Networks for Instancewise Feature Selection

Published: Sep 1, 2019
Abstract
Learning relevant features is important for interpreting data in a machine learning model. Comparing with selecting a relevant feature subset for the entire data, instancewise feature selection is more flexible for model interpretation. However current instancewise feature selection approaches are complex and suffer from high computational cost. We consider instancewise feature selection under supervised learning framework. We design a compact...
Paper Details
Title
Mixture of Deep Neural Networks for Instancewise Feature Selection
Published Date
Sep 1, 2019
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