Unsupervised Feature Selection Based on Ultrametricity and Sparse Training Data: A Case Study for the Classification of High-Dimensional Hyperspectral Data.
Patrick Erik BradleySina KellerMartin WeinmannPublished in: Remote. Sens. (2018)
Keyphrases
- hyperspectral data
- high dimensional
- unsupervised feature selection
- random projections
- hyperspectral
- training data
- hyperspectral images
- classification accuracy
- dimensionality reduction
- hyperspectral imagery
- high dimensionality
- decision trees
- feature selection
- supervised learning
- dimension reduction
- training set
- multispectral
- feature space
- low dimensional
- remote sensing
- infrared
- learning algorithm
- data sets
- class labels
- support vector machine
- high dimensional data
- text classification
- feature vectors
- feature subset
- support vector machine svm
- principal components
- data clustering
- missing data
- pattern recognition
- machine learning