We use the Evolutionary Extreme Learning Machine algorithm, with a specific fitness function to optimize both measures simultaneously, and we compare it with ...
A Hybrid Evolutionary Approach to Obtain Better Quality Classifiers
link.springer.com › content › pdf
Abstract. We present an extra measurement for classifiers, respond- ing to the need to evaluate them with more than accuracy alone. This.
Nov 21, 2024 · A hybrid method that combines BNGE and the k-Nearest Neighbor algorithm, called KBNGE, is introduced for improved classification accuracy.
This article reviews pertinent documents on hybrid frameworks that were published in the period from 2009 to 2022 and offers a thorough analysis of the used ...
A hybrid evolutionary approach to obtain better quality classifiers. Authors, BECERRA ALONSO, DAVID, CARBONERO RUZ, MARIANO, MARTÍNEZ ESTUDILLO, FRANCISCO ...
In this article, a new hybrid approach comprising of two conventional machine learning algorithms has been proposed to carry out attribute selection.
The goal of ranking is to present the most valuable or relevant items at the top of the list, making it easier for users to find what they are looking for.
The experimental results show that the proposed algorithm can achieve better performance than seven state-of-the-art traditional domain adaptation algorithms ...
Missing: Quality | Show results with:Quality
Mar 11, 2023 · This article reviews pertinent documents on hybrid frameworks that were published in the period from 2009 to 2022 and offers a thorough analysis ...
This approach attempts to find certain cross-level rules and possible rules from training data with hierarchical attribute values, yielding more general ...