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Found 5 papers, 3 papers with code
Explain and Conquer: Personalised Text-based Reviews to Achieve Transparency
The items are a subset of users and restaurants and the interactions the reviews posted by these users.
E2E-FS: An End-to-End Feature Selection Method for Neural Networks
Classic embedded feature selection algorithms are often divided in two large groups: tree-based algorithms and lasso variants.
A scalable saliency-based Feature selection method with instance level information
Classic feature selection techniques remove those features that are either irrelevant or redundant, achieving a subset of relevant features that help to provide a better knowledge extraction.
An Information Theory-Based Feature Selection Framework for Big Data Under Apache Spark
With the advent of extremely high dimensional datasets, dimensionality reduction techniques are becoming mandatory.
An Information Theoretic Feature Selection Framework for Big Data under Apache Spark
With the advent of extremely high dimensional datasets, dimensionality reduction techniques are becoming mandatory.
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