Distributed version of RELIEF-F algorithm for Apache Spark.
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Updated
Apr 20, 2018 - Scala
Distributed version of RELIEF-F algorithm for Apache Spark.
Iterative filter-based feature selection on large datasets with Apache Spark
Distributed Rough Set Theory for Feature Selection
My MSc on Data Science final project. This is a library for Data Pre-processing Algorithms for Streaming in Flink (DPASF)
semi-supervised feature selection algorithm for Spark
Image feature selection performed with Apache Spark
Mutual Information functions in Scala
This package contains a generic implementation of greedy Information Theoretic Feature Selection (FS) methods. The implementation is based on the common theoretic framework presented by Gavin Brown. Implementations of mRMR, InfoGain, JMI and other commonly used FS filters are provided.
Harmonizing clinical and genetic data to enhance the precision and efficiency of glioma diagnosis.
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