Feature-ranked self-growing forest: a tree ensemble based on structure diversity for classification and regression.
Ruben I. Carino-EscobarGustavo Adolfo Alonso-SilverioAntonio Alarcón ParedesJessica Cantillo-NegretePublished in: Neural Comput. Appl. (2023)
Keyphrases
- regression problems
- tree structure
- feature vectors
- classifier ensemble
- classification accuracy
- feature set
- support vector
- pattern recognition
- feature selection
- model selection
- training set
- classification method
- classification algorithm
- training data
- feature ranking
- decision tree classifiers
- tree structures
- majority voting
- feature values
- tree ensembles
- individual features
- class labels
- feature space
- supervised feature selection
- neural network
- ensemble learning
- ensemble classifier
- support vector machine
- graph structure
- multiple classifier systems
- feature subset
- cross validation
- final classification
- benchmark datasets
- numeric values
- genetic programming
- image features
- decision forest
- multi variate
- binary decision tree
- base learners
- discriminative features
- classification models
- linear regression
- classification rules
- machine learning methods
- svm classifier
- regression model
- index structure
- image classification
- knn
- feature extraction