decision_tree: Decision Tree Function

In farhanmubasher/tamahagane: Development Tools for R

Description

This function takes two parameters. 1) "formula" will take your model for decision tree. 2) "dataset" will take your data

Usage

decision_tree(formula, dataset)

Arguments

formula	This argument will take your model as input. Model includes a label attribute and some other dependent attributes of same dataset. This function will make decision tree on the base of corelation of Label attribute and other dependent attributes. labelatt ~ att1+att2+att3
dataset	This parameter will take your dataset as input. Data on which you want to perform decision tree.

Details

Your formula/model should be include one label attribute and some other attributes (at least one) and all these (label and other) attributes should be from same dataset. So that this function can take decisions on the base of this given model/formula. You can also use dot (".") if you want to perform this function with one label attribute and for all remaining attributes. So you don't have to write all attributes of dataset in the formula

Value

This function will return some data nodes on the basis of some decisions and then you can plot this data nodes by calling tamahagane.plot() function.

Author(s)

Farhan Mubasher (xululabs)

See Also

tamahagane.plot()

Examples

dt <- tamahagane.decision.tree(Titanic$Survived ~ Age + Gender , Titanic)
dt <- tamahagane.decision.tree(Titanic$Survived ~ . , Titanic)

farhanmubasher/tamahagane documentation built on May 16, 2019, 10:09 a.m.