Contains several functions that allow you to create, visualise, and test Fast and Frugal Trees (FFTrees). FFTrees are very simple decision trees for classifying cases (i.e.; breast cancer patients) into one of two classes (e.g.; no cancer vs. true cancer) based on a small number of cues (e.g.; test results). FFTrees can be preferable to more complex algorithms (such as logistic regression) because they are easy to communicate and implement, and are robust against noisy data.
|Author||Nathaniel Phillips [aut, cre]|
|Date of publication||2016-10-08 21:53:23|
|Maintainer||Nathaniel Phillips <Nathaniel.D.Phillips.firstname.lastname@example.org>|
auc: Calculates AUC (Area under the Curve) using trapezoidal...
bank: A bank marketing dataset
blood: Blood donation dataset
breastcancer: Dataset: Physiological dataset for 699 patients tested for...
car: Car acceptability data
cart.pred: Calculates predictions from CART using the rpart package
classtable: Calculates several classification statistics from binary...
contraceptive: Contraceptive use data
creditapproval: Credit approval data
cuerank: Calculate the marginal accuracy of all cues in a dataframe....
deprecated: Deprecated functions
factclean: Does miscellaneous cleaning of prediction datasets
fertility: Fertility data set
FFTrees: Create Fast and Frugal Trees (FFTrees)
FFTrees.guide: Opens the FFTrees package guide
grow.FFTrees: Grows fast and frugal trees
heartdisease: Heart disease dataset
income: Income dataset
iris: Iris data set
lr.pred: Calculates predictions from logistic regression
mushrooms: Mushrooms dataset
plot.FFTrees: Draws a FFTrees object.
predict.FFTrees: Applies an existing FFTrees object to a new (test) data set
print.FFTrees: Prints summary information from an FFTrees object
showcues: Visualizes cue accuracies in a ROC space
sonar: Sonar data set
summary.FFTrees: Returns a summary of an fft object
titanic: Titanic dataset
voting: Voting data set
wine: Wine tasting dataset