caret v6.0-84

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Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Functions in caret

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

Name
caret.Rmd
train_algo.png
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