Comments (2)
This is in the metrics
module :)
from scikit-plot.
I did not mean the Silhouette analysis plot. I meant a plot where you don't need to know cluster labels. It plots the Silhouette coefficient to determine the optimal number of clusters when you don't know what that is. Much like the elbow plot.
from scikit-plot.
Related Issues (20)
- Is this project still maintained? HOT 1
- add more argument pass through from plot_cumulative_gain to matplotlib
- Add numerical digit precision parameter HOT 1
- The True label displays abnormal HOT 2
- Plot confusion matrix not from predictions but from actual confusion matrix HOT 1
- plot feature importances: how to get the feature names out of a pipeline?
- plot_pca_2d_projection, order of classes/labels is not preserved
- Adding class_names option to gain and lift plots
- Actively Developed? HOT 2
- add class prediction error plot
- Regarding the scikit-plot.metrics.plot_roc function HOT 1
- [BUG] Build status badge not rendering correctly in readme
- Bug: Failing to import Scikitplot fails due to ImportError HOT 4
- Adding a parameter to plot_confusion_matrix() to hide overlaid counts HOT 7
- MatplotlibDeprecationWarning: Passing one of 'on', 'true', 'off', 'false' as a boolean is deprecated
- Too many indices For Array HOT 4
- ValueError: Found input variables with inconsistent numbers of samples HOT 3
- add classes_to_plot option to plot_cumulative_gain HOT 3
- Is there a [problem in precision_recall_curve? HOT 1
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from scikit-plot.