caret v6.0-79


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Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Functions in caret

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