caret v4.17
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by Max Kuhn
Classification and Regression Training
Misc functions for training and plotting classification
and regression models
Functions in caret
Name | Description | |
predictors | List predictors used in the model | |
histogram.train | Lattice functions for plotting resampling results | |
confusionMatrix | Create a confusion matrix | |
findCorrelation | Determine highly correlated variables | |
preProcess | Pre-Processing of Predictors | |
caret-internal | Internal Functions | |
dotPlot | Create a dotplot of variable importance values | |
classDist | Compute and predict the distances to class centroids | |
bagEarth | Bagged Earth | |
bagFDA | Bagged FDA | |
cox2 | COX-2 Activity Data | |
BloodBrain | Blood Brain Barrier Data | |
normalize2Reference | Quantile Normalize Columns of a Matrix Based on a Reference Distribution | |
resampleSummary | Summary of resampled performance estimates | |
mdrr | Multidrug Resistance Reversal (MDRR) Agent Data | |
panel.needle | Needle Plot Lattice Panel | |
format.bagEarth | Format 'bagEarth' objects | |
predict.train | Extract predictions and class probabilities from train objects | |
findLinearCombos | Determine linear combinations in a matrix | |
featurePlot | Wrapper for Lattice Plotting of Predictor Variables | |
maxDissim | Maximum Dissimilarity Sampling | |
pottery | Pottery from Pre-Classical Sites in Italy | |
plotClassProbs | Plot Predicted Probabilities in Classification Models | |
predict.bagEarth | Predicted values based on bagged Earth and FDA models | |
oil | Fatty acid composition of commercial oils | |
postResample | Calculates performance across resamples | |
createDataPartition | Data Splitting functions | |
rfeControl | Controlling the Feature Selection Algorithms | |
plsda | Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis | |
plotObsVsPred | Plot Observed versus Predicted Results in Regression and Classification Models | |
knnreg | k-Nearest Neighbour Regression | |
knn3 | k-Nearest Neighbour Classification | |
Alternate Affy Gene Expression Summary Methods. | Generate Expression Values from Probes | |
createGrid | Tuning Parameter Grid | |
resampleHist | Plot the resampling distribution of the model statistics | |
plot.train | Plot Method for the train Class | |
pcaNNet.default | Neural Networks with a Principal Component Step | |
print.train | Print Method for the train Class | |
aucRoc | Compute the area under an ROC curve | |
normalize.AffyBatch.normalize2Reference | Quantile Normalization to a Reference Distribution | |
plot.varImp.train | Plotting variable importance measures | |
tecator | Fat, Water and Protein Content of Maat Samples | |
predict.knn3 | Predictions from k-Nearest Neighbors | |
lattice.rfe | Lattice functions for plotting resampling results of recursive feature selection | |
varImp | Calculation of variable importance for regression and classification models | |
roc | Compute the points for an ROC curve | |
nearZeroVar | Identification of near zero variance predictors | |
predict.knnreg | Predictions from k-Nearest Neighbors Regression Model | |
applyProcessing | Data Processing on Predictor Variables (Deprecated) | |
spatialSign | Compute the multivariate spatial sign | |
filterVarImp | Calculation of filter-based variable importance | |
train | Fit Predictive Models over Different Tuning Parameters | |
sensitivity | Calculate sensitivity, specificity and predictive values | |
print.confusionMatrix | Print method for confusionMatrix | |
rfe | Backwards Feature Selection | |
as.table.confusionMatrix | Save Confusion Table Results | |
oneSE | Selecting tuning Parameters | |
trainControl | Control parameters for train | |
summary.bagEarth | Summarize a bagged earth or FDA fit | |
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Details
Date | 2009-06-04 |
URL | http://caret.r-forge.r-project.org/ |
License | GPL-2 |
Repository | CRAN |
Repository/R-Forge/Project | caret |
Repository/R-Forge/Revision | 73 |
Date/Publication | 2009-06-05 13:40:16 |
Packaged | 2009-06-05 03:23:01 UTC; rforge |
suggests | ada , affy , caTools , class , e1071 , earth (>= 2.2-3) , elasticnet , ellipse , gbm , glmnet , gpls , grid , ipred , kernlab , klaR , lars , MASS , mboost , mda , mgcv , mlbench , nnet , pamr , party , penalized , pls , proxy , randomForest , relaxo , rpart , RWeka (>= 0.3-14) , sda , SDDA , sparseLDA (>= 0.1-1) , spls , superpc , vbmp |
depends | base (>= 2.5.1) , lattice , R (>= 2.5.1) |
Contributors | Max Contributions from Jed Wing, Steve Weston, Andre Williams, Chris Keefer, Allan Engelhardt |
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