Algorithm recommendation using metalearning

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#Andre Carvalho #IEEE CIS Webinar 2016 #metalearning

A large number of learning algorithms have been developed in the last decades and have been applied to several tasks in different application domains. According to empirical and theoretical results, no single algorithm can outperform the others in every variation of a task. Thus, when using algorithms to solve a new task, we are faced with the question of which algorithm to use. Metalearning provides a general framework for the selection of the most suitable algorithm for a new variation of a given task. This talk will discuss how metalearning can be used for algorithm selection in different tasks.

Metalearning provides a general framework for the selection of the most suitable algorithm for a new variation of a given task. This talk will discuss how metalearning can be used for algorithm selection in different tasks.

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