Visualization Study of High-Dimensional Data Classification Based on PCA-SVM.
Zhongwen ZhaoHuanghuang GuoPublished in: DSC (2017)
Keyphrases
- high dimensional data
- dimensionality reduction
- dimension reduction
- high dimensionality
- low dimensional
- support vector
- support vector machine svm
- high dimensional
- principal component analysis
- feature space
- svm classifier
- linear discriminant analysis
- data analysis
- support vector machine
- feature vectors
- lower dimensional
- feature selection
- data points
- subspace clustering
- high dimensions
- pattern recognition
- input space
- nearest neighbor
- feature extraction
- classification method
- classification algorithm
- regression problems
- subspace learning
- principal components analysis
- dimensionality reduction methods
- small sample size
- variable weighting
- data sets
- machine learning
- training set
- training data
- decision trees
- database
- knn
- random projections
- multi class classification
- similarity search
- face recognition
- dimensional data
- clustering high dimensional data
- data mining
- locally linear embedding
- kernel pca
- high dimensional spaces
- k means
- image data
- model selection
- training samples