AmesImp

<p>A randomly selected subset of the Ames data set.
The dataset has had its values imputed and any remaining NA values removed.</p>

datasets

Provides users the ability to categorize categorical variables dependent on a response variable.
It creates a decision tree by using one of the categorical variables (class factor) and the selected response variable.
The decision tree is created from the rpart() function from the 'rpart' package. The rules from the leaves of
the decision tree are extracted, and used to recategorize the appropriate categorical variable (predictor). This
step is performed for each of the categorical variables that is fed into the data component of
the function. Only variables containing more than 2 factor levels will be considered in the function.
The final output generates a data set containing the recategorized variables or a list containing a mapping table
for each of the candidate variables. For more details see T. Hastie et al (2009, ISBN: 978-0-387-84857-0).

Piro Polo

tree.bins

Recategorization of Factor Variables by Decision Tree Leaves

AmesImp function

<p>A data frame with 2047 observations on 74 variables.</p>

AmesImp: A Subset of the Ames Data Set with Imputed Values

Description

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Examples