ada.classification-package: ada.classification: Classification Methods: K-means and...
In samrabi1/ada.classification: Classification Methods: K-means and Random Forests
Description
This package focuses on problems related to the classification of data into clusters or groups according to the characteristics of the data themselves. Toward this end, it contains functions for convenient implementation of k-means clustering and random forest decision trees with an example data set.
Author(s)
Maintainer: John Duncan Hurt hurt.john@utexas.edu
Authors:
Samantha Rabinowitz samrabi@utexas.edu
samrabi1/ada.classification documentation built on May 23, 2020, 7:01 a.m.
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Description
This package focuses on problems related to the classification of data into clusters or groups according to the characteristics of the data themselves. Toward this end, it contains functions for convenient implementation of k-means clustering and random forest decision trees with an example data set.
Author(s)
Maintainer: John Duncan Hurt hurt.john@utexas.edu
Authors:
Samantha Rabinowitz samrabi@utexas.edu
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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