caret v6.0-78


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Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Functions in caret

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