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If #28244 gets merged, the new `dbcv_score` function will need a user guide. I'm just opening this so we don't lose track of that.
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Hi,
I am obtaining negative values for DBCV scores for multiple clusterings I obtain by varying HDBSCAN hyper-parameters. It is my understanding this is impossible for HDBSCAN. Referring to the pap…
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The CPU hdbscan [library provides](https://github.com/scikit-learn-contrib/hdbscan/blob/c5fcf4b3829d391eadd14598736a763952790a82/hdbscan/hdbscan_.py#L1457) a `relative_validity_` attribute, which is a…
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Hi!
I am running the following code:
db = DBSCAN(eps=5, min_samples=9).fit(df)
labels = db.labels_
dbscan_score = DBCV(df, labels, dist_function=euclidean)
print(dbscan_score)
but I am havi…
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I'm using the validity index in the package, which implements DBCV score according to the following paper:
https://www.dbs.ifi.lmu.de/~zimek/publications/SDM2014/DBCV.pdf
I'm working on a face clu…
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Clustering scores like silhouette work well for K-Means but make less sense for density based clustering techniques like DBSCAN which support arbitrary cluster shapes. It would be nice to include scor…
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On my program your dbcv code return nan in some cases (sklearm Calinski-Harabaz and Shilhuette index work well with this data (3 dimensional, about 200-1000 points)).
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Hi FelSiq
Thanks for having released and for maintaining this DBCV Python package, it is very useful.
I'm writing here today because I tried to use your function on the toy example data used in the …
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Hello,
I'm working with a very large dataset consisting of 7.5 million rows and 18 columns, which represents customer purchase behavior. I initially used UMAP for dimensionality reduction and attem…
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I am working with dataset from a domain of which I'm not an expert. This means that I have neither labels nor ground truth clustering available to me. I am trying to figure out a good way in which I c…