caret v5.03-003

0

Monthly downloads

0th

Percentile

by Max Kuhn

Classification and Regression Training

Misc functions for training and plotting classification and regression models

Functions in caret

Name Description
GermanCredit German Credit Data
avNNet.default Neural Networks Using Model Averaging
knn3 k-Nearest Neighbour Classification
cars Kelly Blue Book resale data for 2005 model year GM cars
bag.default A General Framework For Bagging
classDist Compute and predict the distances to class centroids
bagEarth Bagged Earth
nullModel Fit a simple, non-informative model
bagFDA Bagged FDA
Alternate Affy Gene Expression Summary Methods. Generate Expression Values from Probes
plot.train Plot Method for the train Class
lift Lift Plot
diff.resamples Inferential Assessments About Model Performance
cox2 COX-2 Activity Data
dotplot.diff.resamples Lattice Functions for Visualizing Resampling Differences
maxDissim Maximum Dissimilarity Sampling
caret-internal Internal Functions
normalize.AffyBatch.normalize2Reference Quantile Normalization to a Reference Distribution
normalize2Reference Quantile Normalize Columns of a Matrix Based on a Reference Distribution
plotClassProbs Plot Predicted Probabilities in Classification Models
print.confusionMatrix Print method for confusionMatrix
oil Fatty acid composition of commercial oils
confusionMatrix Create a confusion matrix
dummyVars Create A Full Set of Dummy Variables
postResample Calculates performance across resamples
pcaNNet.default Neural Networks with a Principal Component Step
predict.bagEarth Predicted values based on bagged Earth and FDA models
dhfr Dihydrofolate Reductase Inhibitors Data
predict.train Extract predictions and class probabilities from train objects
featurePlot Wrapper for Lattice Plotting of Predictor Variables
mdrr Multidrug Resistance Reversal (MDRR) Agent Data
plsda Partial Least Squares and Sparse Partial Least Squares Discriminant Analysis
nearZeroVar Identification of near zero variance predictors
histogram.train Lattice functions for plotting resampling results
as.table.confusionMatrix Save Confusion Table Results
format.bagEarth Format 'bagEarth' objects
preProcess Pre-Processing of Predictors
plot.varImp.train Plotting variable importance measures
BloodBrain Blood Brain Barrier Data
prcomp.resamples Principal Components Analysis of Resampling Results
aucRoc Compute the area under an ROC curve
icr.formula Independent Component Regression
BoxCoxTrans.default Box-Cox Transformations
findCorrelation Determine highly correlated variables
confusionMatrix.train Estimate a Resampled Confusion Matrix
modelLookup Descriptions Of Models Available in train()
filterVarImp Calculation of filter-based variable importance
knnreg k-Nearest Neighbour Regression
train Fit Predictive Models over Different Tuning Parameters
predict.knn3 Predictions from k-Nearest Neighbors
panel.needle Needle Plot Lattice Panel
resamples Collation and Visualization of Resampling Results
createGrid Tuning Parameter Grid
findLinearCombos Determine linear combinations in a matrix
sbf Selection By Filtering (SBF)
resampleHist Plot the resampling distribution of the model statistics
caretFuncs Backwards Feature Selection Helper Functions
lattice.rfe Lattice functions for plotting resampling results of recursive feature selection
varImp Calculation of variable importance for regression and classification models
segmentationData Cell Body Segmentation
tecator Fat, Water and Protein Content of Meat Samples
caretSBF Selection By Filtering (SBF) Helper Functions
summary.bagEarth Summarize a bagged earth or FDA fit
oneSE Selecting tuning Parameters
spatialSign Compute the multivariate spatial sign
plotObsVsPred Plot Observed versus Predicted Results in Regression and Classification Models
trainControl Control parameters for train
predictors List predictors used in the model
resampleSummary Summary of resampled performance estimates
rfeControl Controlling the Feature Selection Algorithms
predict.knnreg Predictions from k-Nearest Neighbors Regression Model
print.train Print Method for the train Class
pottery Pottery from Pre-Classical Sites in Italy
roc Compute the points for an ROC curve
createDataPartition Data Splitting functions
dotPlot Create a dotplot of variable importance values
xyplot.resamples Lattice Functions for Visualizing Resampling Results
sbfControl Control Object for Selection By Filtering (SBF)
rfe Backwards Feature Selection
sensitivity Calculate sensitivity, specificity and predictive values
No Results!

Last month downloads

Details

Include our badge in your README

[![Rdoc](http://www.rdocumentation.org/badges/version/caret)](http://www.rdocumentation.org/packages/caret)