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Posted: Tue Jul 11, 2017 8:41 pm
by erhardmenker11
This thread is about the k-means clustering add-in.

k-means clustering is an unsupervised machine learning algorithm that allows for the classification of each observation (across at least 1 series) into 1 of k classes. The algorithm is useful in exploratory data analysis for classifying similarity in observations across a workfile for either cross section or time series data.

The add-in can be downloaded via the EViews Add-in manager or directly from Github at: ... means.aipz
Please refer to the documentation for an overview of the add-in's functionality. Documentation comes with the add-in's install or is available online at: ... kmeans.pdf

Please feel free to post here with any questions or suggestions for improvement. I will also post updates to the add-in in this thread.

Happy modelling,
Erhard Menker