Missing Structural and Clinical Features Imputation for Semi-supervised Alzheimer's Disease Classification using Stacked Sparse Autoencoder.
Emimal JabasonM. Omair AhmadM. N. S. SwamyPublished in: BioCAS (2018)
Keyphrases
- semi supervised
- classification accuracy
- feature space
- feature vectors
- feature set
- missing data
- classification method
- feature extraction
- svm classifier
- class labels
- classification models
- classification process
- missing values
- supervised learning
- structural information
- extracted features
- disease diagnosis
- machine learning
- support vector machine svm
- structural features
- restricted boltzmann machine
- bladder cancer
- multiple imputation
- svm classification
- unsupervised learning
- text classification
- image classification
- image features
- support vector machine
- high dimensional
- labeled and unlabeled data
- multiple sclerosis
- semi supervised learning
- decision trees
- support vector
- label information
- feature selection
- cardiovascular disease
- semi supervised classification
- pairwise
- labeled data