Genetic algorithms as a tool for feature selection in machine learning

By H. Vafaie, Kenneth De Jong. 1992

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Automated Machine Learning: From Principles to Practices (2018, methodology): “…learning configurations, the iterative differentiation methods first iteratively update the model parameter for n steps to obtain 𝑤 𝑛 ( 𝛼 ) for the optimization of lower level objective, and then uses the updated result 𝑤 𝑛 ( 𝛼 ) to approximate ∗ ( 𝛼 ) to obtain the approximated gradient.”
Particle swarm optimization method for image clustering (2005, methodology): “There are several popular supervised algorithms such as the minimum-distance-to-mean, parallelepiped and the Gaussian maximum likelihood classifiers [46].”
GA Tree: genetically evolved decision trees (2000, background): “Punch et al. (1993), Turney (1995), Vafaie & DeJong (1992), Bala et al. (1995) provided more details on this subject.”
Taking Human out of Learning Applications: A Survey on Automated Machine Learning (2018, background): “, greedy search [9] and evolution algorithms [45], [67].”