A B C D E F G H K L M N O P R S T V X
absorp | Fat, Water and Protein Content of Maat Samples |
applyProcessing | Data Processing on Predictor Variables (Deprecated) |
as.matrix.confusionMatrix | Save Confusion Table Results |
as.table.confusionMatrix | Save Confusion Table Results |
aucRoc | Compute the area under an ROC curve |
bagEarth | Bagged Earth |
bagFDA | Bagged FDA |
bbbDescr | Blood Brain Barrier Data |
best | Selecting tuning Parameters |
BloodBrain | Blood Brain Barrier Data |
confusionMatrix | Create a confusion matrix |
cox2 | COX-2 Activity Data |
cox2Class | COX-2 Activity Data |
cox2Descr | COX-2 Activity Data |
cox2IC50 | COX-2 Activity Data |
createDataPartition | Data Splitting functions |
createFolds | Data Splitting functions |
createGrid | Tuning Parameter Grid |
createResample | Data Splitting functions |
defaultSummary | Calculates performance across resamples |
densityplot.train | Lattice functions for plotting resampling results |
dotPlot | Create a dotplot of variable importance values |
endpoints | Fat, Water and Protein Content of Maat Samples |
extractPrediction | Extract predictions and class probabilities from train objects |
extractProb | Extract predictions and class probabilities from train objects |
fattyAcids | Fatty acid composition of commercial oils |
featurePlot | Wrapper for Lattice Plotting of Predictor Variables |
filterVarImp | Calculation of filter-based variable importance |
findCorrelation | Determine highly correlated variables |
findLinearCombos | Determine linear combinations in a matrix |
format.bagEarth | Format 'bagEarth' objects |
generateExprVal.method.trimMean | Generate Expression Values from Probes |
histogram.train | Lattice functions for plotting resampling results |
knn3 | k-Nearest Neighbour Classification |
knn3Train | k-Nearest Neighbour Classification |
logBBB | Blood Brain Barrier Data |
maxDissim | Maximum Dissimilarity Sampling |
mdrr | Multidrug Resistance Reversal (MDRR) Agent Data |
mdrrClass | Multidrug Resistance Reversal (MDRR) Agent Data |
mdrrDescr | Multidrug Resistance Reversal (MDRR) Agent Data |
minDiss | Maximum Dissimilarity Sampling |
nearZeroVar | Identification of near zero variance predictors |
negPredValue | Calculate sensitivity, specificity and predictive values |
normalize.AffyBatch.normalize2Reference | Quantile Normalization to a Reference Distribution |
normalize2Reference | Quantile Normalize Columns of a Matrix Based on a Reference Distribution |
oil | Fatty acid composition of commercial oils |
oilType | Fatty acid composition of commercial oils |
oneSE | Selecting tuning Parameters |
panel.needle | Needle Plot Lattice Panel |
pcaNNet | Neural Networks with a Principal Component Step |
plot.train | Plot Method for the train Class |
plot.varImp.train | Plotting variable importance measures |
plotClassProbs | Plot Predicted Probabilities in Classification Models |
plotObsVsPred | Plot Observed versus Predicted Results in Regression and Classification Models |
plsda | Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis |
posPredValue | Calculate sensitivity, specificity and predictive values |
postResample | Calculates performance across resamples |
pottery | Pottery from Pre-Classical Sites in Italy |
potteryClass | Pottery from Pre-Classical Sites in Italy |
predict.bagEarth | Predicted values based on bagged Earth and FDA models |
predict.bagFDA | Predicted values based on bagged Earth and FDA models |
predict.knn3 | Predictions from k-Nearest Neighbors |
predict.list | Extract predictions and class probabilities from train objects |
predict.pcaNNet | Neural Networks with a Principal Component Step |
predict.plsda | Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis |
predict.preProcess | Pre-Processing of Predictors |
predict.splsda | Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis |
predict.train | Extract predictions and class probabilities from train objects |
predictors | List predictors used in the model |
preProcess | Pre-Processing of Predictors |
print.bagEarth | Bagged Earth |
print.bagFDA | Bagged FDA |
print.confusionMatrix | Print method for confusionMatrix |
print.train | Print Method for the train Class |
processData | Data Processing on Predictor Variables (Deprecated) |
resampleHist | Plot the resampling distribution of the model statistics |
resampleSummary | Summary of resampled performance estimates |
roc | Compute the points for an ROC curve |
sensitivity | Calculate sensitivity, specificity and predictive values |
spatialSign | Compute the multivariate spatial sign |
specificity | Calculate sensitivity, specificity and predictive values |
splsda | Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis |
stripplot.train | Lattice functions for plotting resampling results |
sumDiss | Maximum Dissimilarity Sampling |
summary.bagEarth | Summarize a bagged earth or FDA fit |
summary.bagFDA | Summarize a bagged earth or FDA fit |
tecator | Fat, Water and Protein Content of Maat Samples |
tolerance | Selecting tuning Parameters |
train | Fit Predictive Models over Different Tuning Parameters |
trainControl | Control parameters for train |
varImp | Calculation of variable importance for regression and classification models |
xyplot.train | Lattice functions for plotting resampling results |