Partial least squares classification for high dimensional data using the PCOUT algorithm.
Asuman TurkmenNedret BillorPublished in: Comput. Stat. (2013)
Keyphrases
- high dimensional data
- subspace clustering
- dimension reduction
- preprocessing
- partial least squares
- nearest neighbor
- improved algorithm
- high dimensional
- support vector machine svm
- pattern recognition
- high dimensionality
- learning algorithm
- principal component analysis
- missing values
- dimensional data
- parameter estimation
- dimensionality reduction
- data sets
- decision trees
- data mining
- input data
- low dimensional
- k means
- data analysis
- similarity measure
- machine learning