caret v6.0-34


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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
avNNet.default Neural Networks Using Model Averaging
confusionMatrix.train Estimate a Resampled Confusion Matrix
knn3 k-Nearest Neighbour Classification
diff.resamples Inferential Assessments About Model Performance
normalize.AffyBatch.normalize2Reference Quantile Normalization to a Reference Distribution
Alternate Affy Gene Expression Summary Methods. Generate Expression Values from Probes
plot.train Plot Method for the train Class
featurePlot Wrapper for Lattice Plotting of Predictor Variables
plot.varImp.train Plotting variable importance measures
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
findLinearCombos Determine linear combinations in a matrix
lift Lift Plot
cars Kelly Blue Book resale data for 2005 model year GM cars
print.train Print Method for the train Class
bag.default A General Framework For Bagging
sbf Selection By Filtering (SBF)
update.train Update or Re-fit a Model
format.bagEarth Format 'bagEarth' objects
as.table.confusionMatrix Save Confusion Table Results
createDataPartition Data Splitting functions
knnreg k-Nearest Neighbour Regression
preProcess Pre-Processing of Predictors
plot.rfe Plot RFE Performance Profiles
calibration Probability Calibration Plot
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
nullModel Fit a simple, non-informative model
nearZeroVar Identification of near zero variance predictors
lattice.rfe Lattice functions for plotting resampling results of recursive feature selection
normalize2Reference Quantile Normalize Columns of a Matrix Based on a Reference Distribution
bagFDA Bagged FDA
classDist Compute and predict the distances to class centroids
rfeControl Controlling the Feature Selection Algorithms
filterVarImp Calculation of filter-based variable importance
resampleSummary Summary of resampled performance estimates
postResample Calculates performance across resamples
resampleHist Plot the resampling distribution of the model statistics
summary.bagEarth Summarize a bagged earth or FDA fit
sbfControl Control Object for Selection By Filtering (SBF)
train_model_list A List of Available Models in train
predict.train Extract predictions and class probabilities from train objects
findCorrelation Determine highly correlated variables
print.confusionMatrix Print method for confusionMatrix
caretSBF Selection By Filtering (SBF) Helper Functions
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
trainControl Control parameters for train
oneSE Selecting tuning Parameters
BoxCoxTrans.default Box-Cox and Exponential Transformations
histogram.train Lattice functions for plotting resampling results
confusionMatrix Create a confusion matrix
xyplot.resamples Lattice Functions for Visualizing Resampling Results
downSample Down- and Up-Sampling Imbalanced Data
dhfr Dihydrofolate Reductase Inhibitors Data
resamples Collation and Visualization of Resampling Results
BloodBrain Blood Brain Barrier Data
predict.bagEarth Predicted values based on bagged Earth and FDA models
GermanCredit German Credit Data
spatialSign Compute the multivariate spatial sign
segmentationData Cell Body Segmentation
varImp Calculation of variable importance for regression and classification models
dotPlot Create a dotplot of variable importance values
sensitivity Calculate sensitivity, specificity and predictive values
modelLookup Tools for Models Available in train
dotplot.diff.resamples Lattice Functions for Visualizing Resampling Differences
panel.lift2 Lattice Panel Functions for Lift Plots
dummyVars Create A Full Set of Dummy Variables
maxDissim Maximum Dissimilarity Sampling
plotClassProbs Plot Predicted Probabilities in Classification Models
prcomp.resamples Principal Components Analysis of Resampling Results
oil Fatty acid composition of commercial oils
pottery Pottery from Pre-Classical Sites in Italy
caretFuncs Backwards Feature Selection Helper Functions
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
tecator Fat, Water and Protein Content of Meat Samples
pcaNNet.default Neural Networks with a Principal Component Step
rfe Backwards Feature Selection
bagEarth Bagged Earth
twoClassSim Simulation Functions
predict.knn3 Predictions from k-Nearest Neighbors
icr.formula Independent Component Regression
predictors List predictors used in the model
caret-internal Internal Functions
panel.needle Needle Plot Lattice Panel
cox2 COX-2 Activity Data
train Fit Predictive Models over Different Tuning Parameters
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