7.6 kmeans train
ml train kmeans [options] <k> [csvfile] -o <file.csv> --output=<file.csv> Save the model to csv or movie to mp4 file. --view Popup a movie of the clustering.
With no input csvfile the data is read from standard input which allows the command to be part of a pipeline of commands, whereby the training data (in csv format containing a header) could be piped from another operation.
The default output is a csv of the centres, with a cluster label pre-pended, and a header row with the cluster label column named label.
--output= is provided then the filename extension is used
to determine the type of the output. This is either the model as a
csv file or the movie as an mp4 file. Both can be specified in
ml train kmeans 3 test.csv -o centers.csv -o test.mp4
If no csv output is specified then the output is always to the
terminal, irrespective of whether a mp4 is also output or whether
--view is requested.
The output might look something like:
$ ml train kmeans 3 iris.csv sepal_length,sepal_width,petal_length,petal_width,label 6.85,3.07,5.71,2.05,0 5.00,3.42,1.46,0.24,1 5.88,2.74,4.38,1.43,2
Your donation will support ongoing availability and give you access to the PDF version of this book. Desktop Survival Guides include Data Science, GNU/Linux, and MLHub. Books available on Amazon include Data Mining with Rattle and Essentials of Data Science. Popular open source software includes rattle, wajig, and mlhub. Hosted by Togaware, a pioneer of free and open source software since 1984. Copyright © 1995-2021 Graham.Williams@togaware.com Creative Commons Attribution-ShareAlike 4.0.