Evaluating Interpretability of Multilayer Perceptron and Support Vector Machines for Breast Cancer Classification.
Hajar HakkoumIbtissam AbnaneAli IdriPublished in: AICCSA (2022)
Keyphrases
- multilayer perceptron
- cancer classification
- support vector
- radial basis function
- feature selection
- gene selection
- microarray
- neural network
- random forest
- gene expression data
- cancer diagnosis
- artificial neural networks
- microarray data
- gene expression profiling
- back propagation
- gene expression profiles
- gene expression
- neural network model
- support vector machine
- kernel function
- experimental conditions
- basis functions
- feature ranking
- microarray datasets
- svm classifier
- logistic regression
- loss function
- support vector machine svm
- classification accuracy
- text categorization
- multi class
- prediction accuracy
- training examples
- reinforcement learning
- artificial intelligence