Feature Selection For High Dimensional Data Using Supervised Machine Learning Techniques.
Lazaros KSotiris K. TasoulisAristidis G. VrahatisVassilis P. PlagianakosPublished in: Big Data (2022)
Keyphrases
- high dimensional data
- feature selection
- high dimensionality
- dimensionality reduction
- dimension reduction
- low dimensional
- nearest neighbor
- high dimensional
- gene expression data
- high dimensions
- data sets
- data points
- similarity search
- original data
- data analysis
- subspace clustering
- high dimensional spaces
- data distribution
- subspace learning
- clustering high dimensional data
- dimensional data
- feature extraction
- text classification
- high dimensional data sets
- lower dimensional
- support vector
- small sample size
- text categorization
- variable selection
- nonlinear dimensionality reduction
- feature set
- preprocessing step
- feature selection algorithms
- missing values
- learning algorithm
- manifold learning
- feature subset
- text data
- knn
- machine learning
- database
- selected features
- hyperplane
- pattern recognition
- distance measure
- sparse representation