Contactless and non-destructive chlorophyll content prediction by random forest regression: A case study on fresh-cut rocket leaves.
Dario Pietro CavalloMaria CefolaBernardo PaceAntonio Francesco LogriecoGiovanni AttolicoPublished in: Comput. Electron. Agric. (2017)
Keyphrases
- random forest
- random forests
- decision trees
- prediction accuracy
- ensemble methods
- ensemble classifier
- fold cross validation
- feature set
- regression model
- multi label
- feature importance
- ensemble learning
- base classifiers
- decision tree learning algorithms
- neural network
- text categorization
- genetic programming
- evolutionary algorithm
- feature space