Complete autoencoders for classification with missing values.
Adrián Sánchez-MoralesJosé-Luis Sancho-GómezAníbal R. Figueiras-VidalPublished in: Neural Comput. Appl. (2021)
Keyphrases
- missing values
- cost sensitive learning
- missing data
- data imputation
- feature values
- multivariate temporal data
- incomplete data sets
- incomplete data
- pattern recognition
- data stream classification
- support vector
- classification accuracy
- classification algorithm
- missing attribute values
- missing data imputation
- feature selection
- text classification
- denoising
- machine learning
- cross validation
- data sets
- high dimensional data
- unseen test data
- machine learning algorithms
- image data
- multiple imputation
- missing information
- artificial neural networks
- semi supervised
- supervised learning
- matrix completion
- imputation methods
- feature set
- low rank
- density estimation
- svm classifier