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Clustering Benchmarks

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Clustering Benchmarks

1.1.5

Methodology

Introduction
True vs Predicted Clusters
Noise Points
There Can Be Many Valid Partitions

Benchmark Batteries

Benchmark Suite (v1.1.0)
Explore Datasets (v1.1.0)
Clustering Results Repository (v1.1.0)
File Format Specification
Access from Python, R, MATLAB, etc.
Contributing

Python API

Using clustbench
Documentation
Source Code (GitHub)
PyPI Entry

See Also

Author's Homepage
Data Wrangling in Python
Deep R Programming
genieclust Package

Appendix

Colouriser: A Planar Data Editor
External Cluster Validity Measures
Side Note: Internal (In)Validity Measures
Changelog
References

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Explore Datasets (v1.1.0)¶

A non-interactive dataset catalogue is available here.

Select battery/dataset from the Benchmark Suite (v1.1.0):

/

Preview (only for 1–3 dimensional datasets):

Clustering Results Repository (v1.1.0)

Benchmark Suite (v1.1.0)

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