Supervised Papers Classification on Large-Scale High-Dimensional Data with Apache Spark.
Leonidas AkritidisPanayiotis BozanisAthanasios FevgasPublished in: DASC/PiCom/DataCom/CyberSciTech (2018)
Keyphrases
- high dimensional data
- high dimensionality
- dimensionality reduction
- dimension reduction
- high dimensional
- low dimensional
- nearest neighbor
- regression problems
- unsupervised learning
- feature selection
- subspace clustering
- supervised learning
- data sets
- high dimensions
- small sample size
- feature space
- pattern recognition
- input space
- feature vectors
- machine learning
- data analysis
- text classification
- high dimensional feature spaces
- high dimensional datasets
- real world
- clustering high dimensional data
- sparse representation
- image classification
- dimensionality reduction methods
- supervised dimensionality reduction
- lower dimensional
- nonlinear dimensionality reduction
- multivariate temporal data
- high dimensional data sets
- linear discriminant analysis
- class labels
- similarity search
- model selection
- support vector machine
- data points
- classification algorithm
- high dimensional spaces
- support vector machine svm
- multi dimensional
- support vector
- decision trees
- manifold learning
- dimensional data
- feature extraction
- neural network