caret v6.0-86


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Classification and Regression Training

Misc functions for training and plotting classification and regression models.

Functions in caret

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