rf_regression_pipeline: rf_regression_pipeline
In nearinj/RandomForestUtils: A Pipeline for Running Cross Validated Random Forest Models
Description
Function to run a random forest regression cross validation pipeline. Should not be run by itself. Currently a work in progress.
Usage
1
rf_regression_pipeline(feature_table, actual, SEED = 1995, sampling = NULL)
Arguments
feature_table
The input feature table that contains the features (columns) and samples (rows) that should be used for model training and cross validation.
actual
A vector containing the actual values for the parameter that is being regressed.
SEED
An integer representing the random seed to split samples during cross validation.
nearinj/RandomForestUtils documentation built on July 30, 2020, 9:51 a.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
Function to run a random forest regression cross validation pipeline. Should not be run by itself. Currently a work in progress.
Usage
1 | rf_regression_pipeline(feature_table, actual, SEED = 1995, sampling = NULL)
|
Arguments
feature_table |
The input feature table that contains the features (columns) and samples (rows) that should be used for model training and cross validation. |
actual |
A vector containing the actual values for the parameter that is being regressed. |
SEED |
An integer representing the random seed to split samples during cross validation. |
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.