GFLASSO-LR: Logistic Regression with Generalized Fused LASSO for Gene Selection in High-Dimensional Cancer Classification.
Ahmed Bir-JmelSidi Mohamed DouiriSouad El BernoussiAyyad MaafiriYassine HimeurShadi AtallaWathiq MansoorHussain Al-AhmadPublished in: Comput. (2024)
Keyphrases
- logistic regression
- cancer classification
- gene selection
- generalized linear models
- microarray data
- high dimensional
- gene expression data
- microarray
- feature selection
- cancer diagnosis
- chi square
- random forest
- decision trees
- support vector
- gene expression profiles
- colon cancer
- informative genes
- variable selection
- gene expression
- naive bayes
- high dimensionality
- dna microarray
- loss function
- low dimensional
- microarray analysis
- microarray datasets
- breast cancer
- fold cross validation
- support vector machine svm
- data sets
- dimensionality reduction
- machine learning
- experimental conditions
- text classification
- nearest neighbor
- data points
- classification accuracy
- data analysis
- feature extraction