Sparse PCA with False Discovery Rate Controlled Variable Selection.
Jasin MachkourArnaud BreloyMichael MumaDaniel P. PalomarFrédéric PascalPublished in: CoRR (2024)
Keyphrases
- variable selection
- false discovery rate
- sparse pca
- feature selection
- dimension reduction
- input variables
- model selection
- cross validation
- error rate
- high dimensional
- hypothesis testing
- machine learning
- high dimensionality
- feature space
- support vector
- ls svm
- dimensionality reduction
- data mining techniques
- principal component analysis
- support vector machine
- data sets
- high dimensional data
- supervised learning
- knn
- feature extraction
- decision trees