Neural Networks with Fixed Binary Random Projections Improve Accuracy in Classifying Noisy Data.
Zijin YangAchim SchillingAndreas MaierPatrick KraussPublished in: Bildverarbeitung für die Medizin (2021)
Keyphrases
- noisy data
- random projections
- neural network
- noise tolerant
- high dimensionality
- high dimensional
- compressive sensing
- dimensionality reduction
- learning from noisy data
- pattern recognition
- input data
- dimension reduction
- data sets
- missing data
- machine learning
- least squares
- natural language processing
- nearest neighbor
- low dimensional
- support vector machine svm
- image reconstruction
- missing values
- feature extraction
- decision trees
- feature selection