caret v6.0-62


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