The impact of sample reduction on PCA-based feature extraction for supervised learning.
Mykola PechenizkiySeppo PuuronenAlexey TsymbalPublished in: SAC (2006)
Keyphrases
- feature extraction
- supervised learning
- principal component analysis
- principle component analysis
- reinforcement learning
- feature selection
- unsupervised learning
- feature vectors
- dimension reduction
- pattern classification
- training data
- supervised classification
- training set
- semi supervised
- learning algorithm
- image classification
- image processing
- multiple instance learning
- image preprocessing
- machine learning
- manifold learning
- linear feature extraction
- discriminant analysis
- learning problems
- learning tasks
- frequency domain
- training samples
- wavelet transform
- preprocessing
- support vector machine svm
- statistical learning
- extracted features
- feature representation
- labeled data
- multi class
- supervised machine learning
- feature space
- feature extractors