Classification of high-dimensional data for cervical cancer detection.
Charles BouveyronCamille BrunetVincent VigneronPublished in: ESANN (2009)
Keyphrases
- cancer detection
- high dimensional data
- high dimensionality
- dimension reduction
- high dimensional
- low dimensional
- dimensionality reduction
- data sets
- subspace clustering
- data points
- nearest neighbor
- manifold learning
- small sample size
- prostate cancer
- gene expression data
- clustering high dimensional data
- gene selection
- similarity search
- data analysis
- pattern recognition
- cancer classification
- input space
- classification accuracy
- input data
- decision trees
- lower dimensional
- multivariate temporal data
- computer vision
- high dimensional data sets
- nonlinear dimensionality reduction
- high dimensional datasets
- high dimensional spaces
- image classification
- feature extraction
- x ray images
- feature selection
- training set
- principal component analysis
- database
- machine learning