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clustering-evaluation

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sandipanpaul21 / Clustering-in-Python

Star 31

Clustering methods in Machine Learning includes both theory and python code of each algorithm. Algorithms include K Mean, K Mode, Hierarchical, DB Scan and Gaussian Mixture Model GMM. Interview questions on clustering are also added in the end.

python clustering gaussian-mixture-models clustering-algorithm dbscan kmeans-clustering clustering-evaluation hierarchical-models hierarchical-clustering dbscan-clustering kmeans-algorithm clustering-coefficient clustering-validation clustering-methods dendogram dbscan-algorithm kmeans-analysis dbscan-clusters dbscan-clustering-algorithm k-mode
  • Updated Dec 9, 2021
  • Jupyter Notebook

philips-software / latrend

Star 14
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Support for traj package

niekdt
niekdt commented Jan 14, 2022

The traj package implements a three-step approach and represents trajectories based on 24 characteristics and automatically determines the applicable ones.

This method is very different from currently supported methods in the latrend package, so would be a valuable addition.

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enhancement good first issue

eXascaleInfolab / xmeasures

Star 12

Extremely fast evaluation of the extrinsic clustering measures: various (mean) F1 measures and Omega Index (Fuzzy Adjusted Rand Index) for the multi-resolution clustering with overlaps/covers, standard NMI, clusters labeling

ari clustering-evaluation benchmark-measures nmi f1-score quality-measures omega-index covers-evaluation extrinsic-quality-measures f-measure fuzzy-adjusted-rand-index overlapping-community-evaluation accuracy-metrics
  • Updated Jun 15, 2021
  • C++

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