Importance of feature selection in decision-tree and artificial-neural-network ecological applications. Alburnus alburnus alborella: A practical example.
Tina TirelliDaniela PessaniPublished in: Ecol. Informatics (2011)
Keyphrases
- artificial neural networks
- feature selection
- decision trees
- information gain
- classification models
- machine learning
- naive bayes
- bayes classifier
- neural network
- decision tree induction
- predictive accuracy
- method for feature selection
- logistic regression
- back propagation
- text categorization
- feature set
- feature construction
- text classification
- support vector
- decision tree algorithm
- decision tree learning
- mutual information
- support vector machine
- training data
- bayesian classifier
- multi task
- meta learning
- predictive model
- bayesian networks
- considerable increase
- feature weighting
- relative importance
- random forest
- data sets
- genetic algorithm ga
- dimensionality reduction
- machine learning algorithms
- learning rules
- selected features
- input variables
- classification accuracy
- feed forward
- irrelevant features
- climate change
- unsupervised feature selection
- feature extraction