gap-stat is a Python module that provides a
scikit-learn compatible implementation of the
the gap statistic [1] to estimate the optimal number of clusters
contained in a data set. The module provides the following:
GapStatClustering- a sklearn.cluster compatible wrapper that uses a base clustering estimator to both estimate the optimal number of clusters and generate a clustering with that optimal number of clusters
gapstat- a function that implements the gap statistic algorithm and, if desired, returns the various statistics that were used to estimate the optimal number of clusters
gapstat_score- a sklearn.metrics.cluster compatible function that uses the gap statistic algorithm to provide an evaluation metric for cluster analysis
TBD
gap-stat requires:
- Python (tested with version 3.7.2)
- scikit-learn (tested with version 0.20.1)
- numpy (tested with version 1.15.4)
| [1] | Tibshirani, R. , Walther, G. and Hastie, T. (2001), Estimating the number of clusters in a data set via the gap statistic. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 63: 411-423. doi:10.1111/1467-9868.00293 |