Feature Selection: A literature Review

619 citations recorded by the source corpus.

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FOSTER: Feature Boosting and Compression for Class-Incremental Learning (2022, methodology): “To achieve this, we design a new learning paradigm for class-incremental learning based on feature boosting [13] and compression [31].”
Artificial intelligence in the IVF laboratory: overview through the application of different types of algorithms for the classification of reproductive data (2020, background): “This process consists of determining the relevant data and removing the irrelevant, redundant, and noisy data that offer no useful information [25].”
A comprehensive survey on recent metaheuristics for feature selection (2022, background): “Kumar & Minz introduced the general procedures, fitness evaluation processes, and the basic structures of feature selection [66].”