analyse_predictiveness: Analyse variables predictiveness
In konradsemsch/aider: Perform everyday analytical and data science tasks more efficiently
Description
Usage
Arguments
Examples
Description
This function calculates importance of all variables and selects the ones that are
the most predictive and uncorrelated to each other based on a selected correlation cutoff.
This process is performed iteratively from the most to least important variables. Only numerical
attributes are considered.
Usage
1
analyse_predictiveness(df, target, cutoff)
Arguments
df
A a data frame
target
Target variable
cutoff
Exclude variables that have a correlation higher then a specified threshold
Examples
1
2
data <- recipes::credit_data %>%
first_to_lower()
konradsemsch/aider documentation built on May 22, 2019, 2:40 p.m.
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.
Description Usage Arguments Examples
Description
This function calculates importance of all variables and selects the ones that are the most predictive and uncorrelated to each other based on a selected correlation cutoff. This process is performed iteratively from the most to least important variables. Only numerical attributes are considered.
Usage
1 | analyse_predictiveness(df, target, cutoff)
|
Arguments
df |
A a data frame |
target |
Target variable |
cutoff |
Exclude variables that have a correlation higher then a specified threshold |
Examples
1 2 | data <- recipes::credit_data %>%
first_to_lower()
|
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.