calculate_importance: Find the most important variables
In konradsemsch/aider: Perform everyday analytical and data science tasks more efficiently
Description
Usage
Arguments
Examples
Description
This function calculates importance in a tidy way by extending the filterVarImp() function from caret.
Usage
1
calculate_importance(df, target, type = "classification")
Arguments
df
A a data frame
target
Target variable
type
Type of modelling task. Defaults to classification
Examples
1
2
3
4
5
recipes::credit_data %>%
calculate_importance(Status)
recipes::credit_data %>%
calculate_importance(Status, type = "regression")
konradsemsch/aider documentation built on May 22, 2019, 2:40 p.m.
R Package Documentation
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Description Usage Arguments Examples
Description
This function calculates importance in a tidy way by extending the filterVarImp() function from caret.
Usage
1 | calculate_importance(df, target, type = "classification")
|
Arguments
df |
A a data frame |
target |
Target variable |
type |
Type of modelling task. Defaults to classification |
Examples
1 2 3 4 5 | recipes::credit_data %>%
calculate_importance(Status)
recipes::credit_data %>%
calculate_importance(Status, type = "regression")
|
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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