WEKA Clustering Workflows

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This section describes workflows using the Weka Machine Learning library for clustering data and following visualisation of the results.

Weka Clustering With Silhouette Analysis As PDF

This workflow clusters given QSAR CSV file and performs a silhouette analysis which is visualised in a PDF file. Therefor it loads the QSAR data from a file and converts it into the Weke dataformat. After that the data is clustered and the results are safed to a PDF file.
Go to MyExperiment

(l.) Configuration panel of the clustering activity. (r.) The clustering workflow.

Configuration annotations:

  • Set the list handling of the second activity to dot product.
Example results.

Weka Clustering Clustering Considering Different Origins Result As PDF

This workflow clusters the given CSV files with the chosen Weka algorithm. The results are visualized in a PDF file. Therefor the CSV files are loaded from hard disk and merged together. Afterwards they are converted into a Weka dataset which is the suitable data type for the Weka clustering activity.
Go to MyExperiment

Weka Clustering Considering Different Origins Result As PDF workflow.

Configuration annotations:

  • Set the list handling of activity 1,2,3 to dot product.
Weka clustering result example.

Contact

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