Gene Selection and Classification in Microarray Datasets Using a Hybrid Approach of PCC-BPSO/GA With Multi Classifiers

Journal of Computer Science - United States
doi 10.3844/jcssp.2018.868.880
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Science Publications

Related search

An Efficient Gene Selection Method for Microarray Data Based on LASSO and BPSO

BMC Bioinformatics
BiochemistryApplied MathematicsComputer Science ApplicationsStructural BiologyMolecular Biology
2019English

A Novel Microarray Gene Selection and Classification Using Intelligent Dynamic Grey Wolf Optimization

Genetika
AgriculturalPlant ScienceGeneticsBiological Sciences
2019English

A Novel Parametric Approach to Mine Gene Regulatory Relationship From Microarray Datasets

BMC Bioinformatics
BiochemistryApplied MathematicsComputer Science ApplicationsStructural BiologyMolecular Biology
2010English

Robust Feature Selection Approach for Patient Classification Using Gene Expression Data

Bioinformation
2017English

Feature Selection and Ensemble Hierarchical Cluster-Based Under-Sampling Approach for Extremely Imbalanced Datasets: Application to Gene Classification

2011English

Sentiment Reviews Classification Using Hybrid Feature Selection

International Journal of Database Theory and Application
Computer Science
2017English

Multi-Category News Classification Using Support Vector Machine Based Classifiers

SN Applied Sciences
2020English

A Hybrid Approach for Feature Subset Selection Using Ant Colony Optimization and Multi-Classifier Ensemble

International Journal of Advanced Computer Science and Applications
Computer Science
2018English

Heuristic Selection in a Multi-Phase Hybrid Approach for Dynamic Environments

2012English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy