Feature Selection and Hyperparameter Fine-Tuning in Artificial Neural Networks for Wood Quality Classification.
Mateus RoderLeandro Aparecido PassosJoão Paulo PapaAndré Luis Debiaso RossiPublished in: BRACIS (2) (2023)
Keyphrases
- fine tuning
- feature selection
- artificial neural networks
- classification accuracy
- text classification
- model selection
- machine learning
- support vector
- feature space
- classification models
- feature extraction
- high quality
- high dimensionality
- feature set
- fine tune
- feature selection algorithms
- neural network
- support vector machine
- mutual information
- unsupervised learning
- decision trees
- viable alternative
- image classification
- pattern recognition
- text categorization
- method for feature selection
- discriminative features
- feature subset
- small sample
- classification method
- naive bayes
- bayes classifier
- accurate classification
- classification performances
- wrapper feature selection
- class separability
- neural network model
- dimensionality reduction
- computational intelligence
- supervised learning
- using artificial neural networks
- multi layer perceptron
- fold cross validation
- hyperparameters
- svm classifier
- support vector machine svm
- training set
- feature selection and classification
- learning algorithm
- support vector classification
- genetic algorithm