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All functions

BestCut()
Best Cutpoint for a ROC Curve
BreuschPaganTest()
Breusch-Pagan Test
CP() print(<CP>) plot(<CP>)
Complexity Parameter of an rpart Model
CoeffDiffCI()
Confidence Interval for the Difference of Two Coefficients in a Linear Model
FitMod() predict(<FitMod>) plot(<FitMod>) summary(<FitMod>) drop1(<FitMod>)
Wrapper for Several Model Functions
LeafRates() plot(<LeafRates>)
Leafrates for the Nodes of an 'rpart' Tree
LogitBoost()
LogitBoost Classification Algorithm
ModTools-package ModTools
Regression and Classification Tools
Node()
Nodes and Splits in an rpart Tree
OverSample() UnderSample()
Oversample and Undersample
PlotLift()
Lift Charts to Compare Binary Predictive Models
PredictCI()
Confidence Intervals for Predictions of a GLM
ROC()
Build a ROC curve
RefLevel()
Used Reference Levels in a Linear Model
Response()
Extract the Response from Several Models
RobSummary()
Robust Summary for Linear Models
Rules()
Extract Rules from 'rpart' Object
SplitTrainTest()
Split DataFrame in Train an Test Sample
TModC() plot(<TModC>)
Compare Classification Models
Tune()
Tune Classificators
VarImp() plot(<VarImp>) print(<VarImp>)
Variable Importance for Regression and Classification Models
d.glass
Measurements of Forensic Glass Fragments
d.pima d.pima2
Diabetes survey on Pima Indians
Tobit()
Tobit Regression