caret v6.0-76


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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
bagFDA Bagged FDA
calibration Probability Calibration Plot
createDataPartition Data Splitting functions
densityplot.rfe Lattice functions for plotting resampling results of recursive feature
featurePlot Wrapper for Lattice Plotting of Predictor Variables
filterVarImp Calculation of filter-based variable importance
knnreg k-Nearest Neighbour Regression
learing_curve_dat Create Data to Plot a Learning Curve
oneSE Selecting tuning Parameters
panel.lift2 Lattice Panel Functions for Lift Plots
plotClassProbs Plot Predicted Probabilities in Classification Models
predict.gafs Predict new samples
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification
predict.knn3 Predictions from k-Nearest Neighbors
rfeControl Controlling the Feature Selection Algorithms
safs Simulated annealing feature selection
negPredValue Calculate sensitivity, specificity and predictive values
spatialSign Compute the multivariate spatial sign
xyplot.resamples Lattice Functions for Visualizing Resampling Results
caret-internal Internal Functions
pickSizeBest Backwards Feature Selection Helper Functions
downSample Down- and Up-Sampling Imbalanced Data
dummyVars Create A Full Set of Dummy Variables
histogram.train Lattice functions for plotting resampling results
icr.formula Independent Component Regression
lift Lift Plot
maxDissim Maximum Dissimilarity Sampling
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
postResample Calculates performance across resamples
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
extractPrediction Extract predictions and class probabilities from train objects
scat Morphometric Data on Scat
segmentationData Cell Body Segmentation
varImp.gafs Variable importances for GAs and SAs
var_seq Sequences of Variables for Tuning
bag A General Framework For Bagging
bagEarth Bagged Earth
classDist Compute and predict the distances to class centroids
confusionMatrix Create a confusion matrix
dhfr Dihydrofolate Reductase Inhibitors Data
diff.resamples Inferential Assessments About Model Performance
format.bagEarth Format 'bagEarth' objects
gafs.default Genetic algorithm feature selection
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
modelLookup Tools for Models Available in
plot.gafs Plot Method for the gafs and safs Classes
ggplot.rfe Plot RFE Performance Profiles
preProcess Pre-Processing of Predictors
predict.bagEarth Predicted values based on bagged Earth and FDA models
resamples Collation and Visualization of Resampling Results
rfe Backwards Feature Selection
BloodBrain Blood Brain Barrier Data
BoxCoxTrans Box-Cox and Exponential Transformations
confusionMatrix.train Estimate a Resampled Confusion Matrix
cox2 COX-2 Activity Data
dotPlot Create a dotplot of variable importance values
dotplot.diff.resamples Lattice Functions for Visualizing Resampling Differences
index2vec Convert indicies to a binary vector
knn3 k-Nearest Neighbour Classification
train_model_list A List of Available Models in train
nearZeroVar Identification of near zero variance predictors
ggplot.train Plot Method for the train Class
plot.varImp.train Plotting variable importance measures
gafsControl Control parameters for GA and SA feature selection
safs_initial Ancillary simulated annealing functions
summary.bagEarth Summarize a bagged earth or FDA fit
tecator Fat, Water and Protein Content of Meat Samples
GermanCredit German Credit Data
Sacramento Sacramento CA Home Prices
caretSBF Selection By Filtering (SBF) Helper Functions
cars Kelly Blue Book resale data for 2005 model year GM cars
gafs_initial Ancillary genetic algorithm functions
getSamplingInfo Get sampling info from a train model
nullModel Fit a simple, non-informative model
oil Fatty acid composition of commercial oils
pottery Pottery from Pre-Classical Sites in Italy
prcomp.resamples Principal Components Analysis of Resampling Results
print.train Print Method for the train Class
recall Calculate recall, precision and F values
sbf Selection By Filtering (SBF)
sbfControl Control Object for Selection By Filtering (SBF)
SLC14_1 Simulation Functions
update.safs Update or Re-fit a SA or GA Model
as.matrix.confusionMatrix Confusion matrix as a table
avNNet Neural Networks Using Model Averaging
findCorrelation Determine highly correlated variables
findLinearCombos Determine linear combinations in a matrix
panel.needle Needle Plot Lattice Panel
pcaNNet Neural Networks with a Principal Component Step
predictors List predictors used in the model
print.confusionMatrix Print method for confusionMatrix
resampleHist Plot the resampling distribution of the model statistics
resampleSummary Summary of resampled performance estimates
train Fit Predictive Models over Different Tuning Parameters
trainControl Control parameters for train
update.train Update or Re-fit a Model
varImp Calculation of variable importance for regression and classification models
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