Multi-class computational evolution: development, benchmark evaluation and application to RNA-Seq biomarker discovery

Multi-class computational evolution: development, benchmark evaluation and application to RNA-Seq biomarker discovery

Abstract Background A computational evolution system (CES) is a knowledge discovery engine that can identify subtle, synergistic relationships in large datasets. Pareto optimization allows CESs to balance accuracy with model complexity when evolving classifiers. Using Pareto optimization, a CES is a...

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Bibliographic Details
Main Authors: Nathaniel M. Crabtree, Jason H. Moore, John F. Bowyer, Nysia I. George
Format: Article
Language:English
Published: BMC 2017-04-01
Series:BioData Mining
Subjects:
Artificial intelligence
Feature selection
Classification
Genetic programming
Machine learning
Data mining
Online Access:http://link.springer.com/article/10.1186/s13040-017-0134-8

Internet

http://link.springer.com/article/10.1186/s13040-017-0134-8

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