process_cat_feats: Process categorical features
In SchlossLab/mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines
process_cat_feats R Documentation
Process categorical features
Description
Process categorical features
Usage
process_cat_feats(features, progbar = NULL)
Arguments
features
dataframe of features for machine learning
progbar
optional progress bar (default: NULL)
Value
list of two dataframes: categorical (processed) and continuous features (unprocessed)
Author(s)
Zena Lapp, zenalapp@umich.edu
Examples
## Not run:
process_cat_feats(mikropml::otu_small[, 2:ncol(otu_small)])
## End(Not run)
SchlossLab/mikropml documentation built on Aug. 24, 2023, 9:51 p.m.
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| process_cat_feats | R Documentation |
Process categorical features
Description
Process categorical features
Usage
process_cat_feats(features, progbar = NULL)
Arguments
features |
dataframe of features for machine learning |
progbar |
optional progress bar (default: |
Value
list of two dataframes: categorical (processed) and continuous features (unprocessed)
Author(s)
Zena Lapp, zenalapp@umich.edu
Examples
## Not run:
process_cat_feats(mikropml::otu_small[, 2:ncol(otu_small)])
## End(Not run)
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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