Multivariate random forests
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Summary
The genesis of, and motivation for, the random forest paradigm as an outgrowth from earlier tree‐structured techniques is outlined and an illustrative example from ecology is provided that showcases the improved fit and enhanced interpretation afforded by the random Forest framework.
- Type
- article
- Published
- 2011-01-01
- Cited by
- 269
- References
- 25
- OpenAlex
- https://openalex.org/W2084714454
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:18976374
Keywords
Random forest, Computer science, Multivariate statistics, Schema (genetic algorithms), Machine learning
References
- Classification and Regression by randomForest
- Finding Groups in Data: An Introduction to Cluster Analysis
- Gentleman R: R: A language for data analysis and graphics
- Classification Trees for Multiple Binary Responses
- Random Forests and Adaptive Nearest Neighbors
- Classification and regression trees
- Tree-Structured Methods for Longitudinal Data
- Arcing classifier (with discussion and a rejoinder by the author)
- The Elements of Statistical Learning
- Identification of Yeast Transcriptional Regulation Networks Using Multivariate Random Forests
- Statistical Modeling: The Two Cultures (with comments and a rejoinder by the author)
- Constructing decision trees with multiple response variables
- MULTIVARIATE REGRESSION TREES: A NEW TECHNIQUE FOR MODELING SPECIES–ENVIRONMENT RELATIONSHIPS
- An Introduction to the Bootstrap
- Random Forests
- Bagging Predictors
- MULTIVARIATE REGRESSION TREES: A NEW TECHNIQUE FOR MODELING SPECIES-ENVIRONMENT RELATIONSHIPS
- An Introduction to the Bootstrap
- Arcing Classifiers
- Relating HIV-1 Sequence Variation to Replication Capacity via Trees and Forests
Cited by
- Improvements to random forest methodology
- Joint prediction of multiple scores captures better individual traits from brain images
- Canonical Correlation Forests
- Support vector machines in engineering: an overview
- Proteomics-based, multivariate random forest method for prediction of protein separation behavior during cation-exchange chromatography.
- Spatial attributes of fire regime in eastern Canada: influences of regional landscape physiography and climate
- Multi-objective optimization of ensemble of regression trees using genetic algorithms
- Case-Specific Random Forests
- Random forests on Hadoop for genome-wide association studies of multivariate neuroimaging phenotypes
- A multivariate random forest based framework for drug sensitivity prediction
- A Bayesian regression tree approach to identify the effect of nanoparticles’ properties on toxicity profiles
- Random forests on distance matrices for imaging genetics studies
- MULTI-OUTPUT RANDOM FORESTS
- Effects of spatial scale and choice of statistical model (linear versus tree-based) on determining species-habitat relationships
- A refinement of models projecting future Canadian fire regimes using homogeneous fire regime zones
- Finding structure in data using multivariate tree boosting
- Multivariate random forest models of estuarine-associated fish and invertebrate communities
- Predictor augmentation in random forests
- Seascape context and predators override water quality effects on inshore coral reef fish communities
- Mapping Fractional Land Use and Land Cover in a Monsoon Region: The Effects of Data Processing Options
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