Last data update: 2014.03.03

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R Release (3.2.3)
CranContrib
BioConductor
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Results 71 - 80 of 182600 found.
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na.roughfix (Package: randomForest) : Rough Imputation of Missing Values

Impute Missing Values by median/mode.
● Data Source: CranContrib
● Keywords: NA
● Alias: na.roughfix, na.roughfix.data.frame, na.roughfix.default
● 0 images

varImpPlot (Package: randomForest) : Variable Importance Plot

Dotchart of variable importance as measured by a Random Forest
● Data Source: CranContrib
● Keywords: classif, regression, tree
● Alias: varImpPlot
● 0 images

plot.randomForest (Package: randomForest) : Plot method for randomForest objects

Plot the error rates or MSE of a randomForest object
● Data Source: CranContrib
● Keywords: classif, regression, tree
● Alias: plot.randomForest
● 0 images

rfImpute (Package: randomForest) : Missing Value Imputations by randomForest

Impute missing values in predictor data using proximity from randomForest.
● Data Source: CranContrib
● Keywords: classif, regression, tree
● Alias: rfImpute, rfImpute.default, rfImpute.formula
● 0 images

rfcv (Package: randomForest) : Random Forest Cross-Valdidation for feature selection

This function shows the cross-validated prediction performance of models with sequentially reduced number of predictors (ranked by variable importance) via a nested cross-validation procedure.
● Data Source: CranContrib
● Keywords: classif, regression
● Alias: rfcv
● 0 images

treesize (Package: randomForest) : Size of trees in an ensemble

Size of trees (number of nodes) in and ensemble.
● Data Source: CranContrib
● Keywords: classif, regression
● Alias: treesize
● 0 images

predict.randomForest (Package: randomForest) : predict method for random forest objects

Prediction of test data using random forest.
● Data Source: CranContrib
● Keywords: classif, regression
● Alias: predict.randomForest
● 0 images

importance (Package: randomForest) : Extract variable importance measure

This is the extractor function for variable importance measures as produced by randomForest.
● Data Source: CranContrib
● Keywords: classif, regression, tree
● Alias: importance, importance.default, importance.randomForest
● 0 images

mini (Package: randomGLM) : An example data set derived from the brain cancer data set

This example contains one training set, one test set, a corresponding binary outcome and a corresponding continuous outcome. Outcomes are gene traits derived from the brain cancer data set.
● Data Source: CranContrib
● Keywords:
● Alias: mini
● 0 images

brainCancer (Package: randomGLM) : The brain cancer data set

2 sets containing the gene expression profiles of 55 and 65 brain cancer patients respectively.
● Data Source: CranContrib
● Keywords:
● Alias: brainCancer
● 0 images