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