# caret v2.29

0

Monthly downloads

by Max Kuhn

## Classification and Regression Training

Misc functions for training and plotting classification and regression models

## Functions in caret

Name | Description | |

BloodBrain | Blood Brain Barrier Data | |

bagFDA | Bagged FDA | |

createGrid | Tuning Parameter Grid | |

bagEarth | Bagged Earth | |

cox2 | COX-2 Activity Data | |

confusionMatrix | Create a confusion matrix | |

normalize2Reference | Quantile Normalize Columns of a Matrix Based on a Reference Distribution | |

varImp | Calculation of variable importance for regression and classification models | |

createDataPartition | Data Splitting functions | |

Alternate Affy Gene Expression Summary Methods. | Generate Expression Values from Probes | |

plot.varImp.train | Plotting variable importance measures | |

dotPlot | Create a dotplot of variable importance values | |

mdrr | Multidrug Resistance Reversal (MDRR) Agent Data | |

resampleHist | Plot the resampling distribution of the model statistics | |

print.confusionMatrix | Print method for confusionMatrix | |

pottery | Pottery from Pre-Classical Sites in Italy | |

tecator | Fat, Water and Protein Content of Maat Samples | |

normalize.AffyBatch.normalize2Reference | Quantile Normalization to a Reference Distribution | |

filterVarImp | Calculation of filter-based variable importance | |

train | Fit Predictive Models over Different Tuning Parameters | |

sensitivity | Calculate Sensitivity, Specificity and predictive values | |

trainControl | Control parameters for train | |

roc | Compute the points for an ROC curve | |

extractPrediction | Extract predictions and class probabilities from train objects | |

findCorrelation | Determine highly correlated variables | |

spatialSign | Compute the multivariate spatial sign | |

plot.train | Plot Method for the train Class | |

summary.bagEarth | Summarize a bagged earth or FDA fit | |

oil | Fatty acid composition of commercial oils | |

plsda | Partial Least Squares Discriminant Analysis | |

aucRoc | Compute the area under an ROC curve | |

featurePlot | Wrapper for Lattice Plotting of Predictor Variables | |

nearZeroVar | Identification of near zero variance predictors | |

predict.bagEarth | Predicted values based on bagged Earth and FDA models | |

panel.needle | Needle Plot Lattice Panel | |

print.train | Print Method for the train Class | |

caret-internal | Internal Functions | |

resampleSummary | Summary of resampled performance estimates | |

findLinearCombos | Determine linear combinations in a matrix | |

plotObsVsPred | Plot Observed versus Predicted Results in Regression and Classification Models | |

postResample | Calculates performance across resamples | |

predict.knn3 | Predictions from k-Nearest Neighbors | |

plotClassProbs | Plot Predicted Probabilities in Classification Models | |

knn3 | k-Nearest Neighbour Classification | |

maxDissim | Maximum Dissimilarity Sampling | |

applyProcessing | Data Processing on Predictor Variables | |

No Results! |

## Last month downloads

## Details

Date | 2007-10-08 |

License | GPL 2.0 |

Packaged | Tue Oct 9 08:54:23 2007; kuhna03 |

suggests | ada , affy , class , e1071 , earth , ellipse , gam , gbm , gpls , grid , ipred , kernlab , klaR , MASS , mboost , mda , mgcv , mlbench , nnet , pamr , party , pls , proxy , randomForest , rpart |

depends | base (>= 2.1.0) , lattice , R (>= 2.1.0) |

Contributors | Steve Weston, Andre Williams, Max Kuhn, Jed Wing |

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