A Machine Learning Pipeline for Cancer Detection on Microarray Data: The Role of Feature Discretization and Feature Selection
Early disease detection using microarray data is vital for prompt and efficient treatment. However, the intricate nature of these data and the ongoing need for more precise interpretation techniques make it a persistently active research field. Numerous gene expression datasets are publicly availabl...
Main Authors: | Adara Nogueira, Artur Ferreira, Mário Figueiredo |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-08-01
|
Series: | BioMedInformatics |
Subjects: | |
Online Access: | https://www.mdpi.com/2673-7426/3/3/40 |
Similar Items
-
FEATURE SELECTION IN THE TASK OF MEDICAL DIAGNOSTICS ON MICROARRAY DATA
by: N. G. Zagoruiko, et al.
Published: (2015-01-01) -
Importance of feature selection stability in the classifier evaluation on high-dimensional genetic data
by: Tomasz Łukaszuk, et al.
Published: (2024-11-01) -
Feature selection of gene expression data for Cancer classification using double RBF-kernels
by: Shenghui Liu, et al.
Published: (2018-10-01) -
A comprehensive learning based swarm optimization approach for feature selection in gene expression data
by: Subha Easwaran, et al.
Published: (2024-09-01) -
A Mutual Information estimator for continuous and discrete variables applied to Feature Selection and Classification problems
by: Frederico Coelho, et al.
Published: (2016-08-01)