imp_var_EAT: Breiman's Variable Importance
In MiriamEsteve/EAT: Efficiency Analysis Trees
Description
Usage
Arguments
Value
Description
This function recalculates all the possible splits, with the exception of the one being used, and for each node and variable gets the best split based on their degree of importance.
Usage
1
imp_var_EAT(data, tree, x, y, digits)
Arguments
data
Data from EAT object.
tree
Tree from EAT object.
x
Column input indexes in data.
y
Column output indexes in data.
digits
Decimal units.
Value
A dataframe with the best split for each node and its variable importance.
MiriamEsteve/EAT documentation built on Jan. 18, 2022, 6:55 p.m.
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Description Usage Arguments Value
Description
This function recalculates all the possible splits, with the exception of the one being used, and for each node and variable gets the best split based on their degree of importance.
Usage
1 | imp_var_EAT(data, tree, x, y, digits)
|
Arguments
data |
Data from EAT object. |
tree |
Tree from EAT object. |
x |
Column input indexes in data. |
y |
Column output indexes in data. |
digits |
Decimal units. |
Value
A dataframe with the best split for each node and its variable importance.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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