Comments (5)
And a gallery!
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@bbengfort Working on addressing this very minimally right now, will push preliminary description to README momentarily.
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@rebeccabilbro ok sounds good; I'm almost done with the examples notebook - have to do some minor massaging of the classifiers.
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@bbengfort Ok, pushed to README: https://github.com/DistrictDataLabs/yellowbrick/blob/develop/README.md. Here's the snippet:
Using Yellowbrick
The Yellowbrick API is specifically designed to play nicely with Scikit-Learn. Here is an example of a typical workflow sequence with Scikit-Learn and Yellowbrick:
Feature Visualization
In this example, we see how Rank2D performs pairwise comparisons of each feature in the data set with a specific metric or algorithm, then returns them ranked as a lower left triangle diagram.
from yellowbrick.features import Rank2D
visualizer = Rank2D(features=features, algorithm='covariance')
visualizer.fit(X, y) # Fit the data to the visualizer
visualizer.transform(X) # Transform the data
visualizer.poof() # Draw/show/poof the data
Model Visualization
In this example, we instantiate a Scikit-Learn classifier, and then we use Yellowbrick's ROCAUC class to visualize the tradeoff between the classifier's sensitivity and specificity.
from sklearn.svm import LinearSVC
from yellowbrick import ROCAUC
model = LinearSVC()
model.fit(X,y)
y_pred = model.predict(X)
visualizer = ROCAUC(model)
visualizer.score(y,y_pred)
visualizer.poof()
For additional information on getting started with Yellowbrick, check out our quick start guide.
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@rebeccabilbro looks great! The only thing I'd add is we probably want to point people to the examples rather than the quick start guide which doesn't appear to be complete.
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Related Issues (20)
- How not to plot legend in RadViz plot? HOT 4
- On the generation of RadViz plot HOT 1
- Use classification visualizers directly from predictions, targets and logits? HOT 1
- [SilhouetteVisualizer] Constructor argument is_fitted is ignored during initialization HOT 1
- ConfusionMatrix visualizer error with sklearn models HOT 3
- Is there a way to hide the figure from KElbowVisualizer? HOT 3
- Let `KElbowVisualizer` use all the distance metrics supported by sklearn HOT 5
- The PredictionError can't be visualized due to the dim error HOT 2
- Adjusting markersize in `prediction_error` HOT 2
- Matplotlib warning about color usage in Datasaurus
- No figure output of the show method and produce a lot of findfont: Generic family 'sans-serif' not found warnings HOT 2
- Unable to use Silhouette Visualizer with Gaussian Mixture Model HOT 7
- Can't plot class report with trained model HOT 1
- Interactive plots - support plotly backend. HOT 4
- InterclusterDistance AttributeError: 'NoneType' object has no attribute '_get_renderer' HOT 2
- Add arguments to change PCA biplot arrow and arrow label colors and other properties HOT 1
- yellowbrics conflict with matplotlib: use_line_collection in cause!
- Classification report shows classes inverted if passed from sklearn label encoder
- CooksDistance regressor generating error
- Yellowbrick no updated since 1 year ago?! HOT 1
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