Evolution of SOMs' Structure and Learning Algorithm: From Visualization of High-Dimensional Data to Clustering of Complex Data.
Marian B. GorzalczanyFilip RudzinskiPublished in: Algorithms (2020)
Keyphrases
- high dimensional data
- complex data
- self organizing maps
- data analysis
- low dimensional
- learning algorithm
- dimensionality reduction
- high dimensionality
- subspace clustering
- nearest neighbor
- data points
- high dimensional
- multidimensional scaling
- data sets
- high dimensions
- dimension reduction
- similarity search
- low dimensional structure
- cluster structure
- high dimensional data sets
- input data
- manifold learning
- linear discriminant analysis
- underlying manifold
- nonlinear dimensionality reduction
- high dimensional datasets
- clustering high dimensional data
- machine learning
- training data
- neural network
- dimensional data
- feature space
- input space
- high dimensional spaces
- feature selection
- lower dimensional
- computer vision
- data visualization
- areas of data mining
- image processing
- supervised learning