A Literature Survey and Empirical Study of Meta-Learning for Classifier Selection

A Literature Survey and Empirical Study of Meta-Learning for Classifier Selection

Classification is the key and most widely studied paradigm in machine learning community. The selection of appropriate classification algorithm for a particular problem is a challenging task, formally known as algorithm selection problem (ASP) in literature. It is increasingly becoming focus of rese...

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Bibliographic Details
Main Authors: Irfan Khan, Xianchao Zhang, Mobashar Rehman, Rahman Ali
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Meta-learning
algorithm selection
classification
machine learning
Online Access:https://ieeexplore.ieee.org/document/8951014/

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