tuneRF
(Package: randomForest) :
Tune randomForest for the optimal mtry parameter
Starting with the default value of mtry, search for the optimal value (with respect to Out-of-Bag error estimate) of mtry for randomForest.
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: tuneRF
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combine
(Package: randomForest) :
Combine Ensembles of Trees
Combine two more more ensembles of trees into one.
● Data Source:
CranContrib
● Keywords: classif, regression
● Alias: combine
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randomForest
(Package: randomForest) :
Classification and Regression with Random Forest
randomForest implements Breiman's random forest algorithm (based on Breiman and Cutler's original Fortran code) for classification and regression. It can also be used in unsupervised mode for assessing proximities among data points.
● Data Source:
CranContrib
● Keywords: classif, regression, tree
● Alias: print.randomForest, randomForest, randomForest.default, randomForest.formula
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varUsed
(Package: randomForest) :
Variables used in a random forest
Find out which predictor variables are actually used in the random forest.
● Data Source:
CranContrib
● Keywords: tree
● Alias: varUsed
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grow
(Package: randomForest) :
Add trees to an ensemble
Add additional trees to an existing ensemble of trees.
● Data Source:
CranContrib
● Keywords: classif, regression
● Alias: grow, grow.default, grow.randomForest
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getTree
(Package: randomForest) :
Extract a single tree from a forest.
This function extract the structure of a tree from a randomForest object.
● Data Source:
CranContrib
● Keywords: tree
● Alias: getTree
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Prototypes are ‘representative’ cases of a group of data points, given the similarity matrix among the points. They are very similar to medoids. The function is named ‘classCenter’ to avoid conflict with the function prototype in the methods package.
● Data Source:
CranContrib
● Keywords: classif
● Alias: classCenter
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MDSplot
(Package: randomForest) :
Multi-dimensional Scaling Plot of Proximity matrix from randomForest
Plot the scaling coordinates of the proximity matrix from randomForest.
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: MDSplot
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outlier
(Package: randomForest) :
Compute outlying measures
Compute outlying measures based on a proximity matrix.
● Data Source:
CranContrib
● Keywords: classif
● Alias: outlier, outlier.default, outlier.randomForest
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Partial dependence plot gives a graphical depiction of the marginal effect of a variable on the class probability (classification) or response (regression).
● Data Source:
CranContrib
● Keywords: classif, regression, tree
● Alias: partialPlot, partialPlot.default, partialPlot.randomForest
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