Tutorial on creating random forest classifier #1052
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If you merge master (or rebase on master), this should pass CI. |
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| GitGuardian id | Secret | Commit | Filename | |
|---|---|---|---|---|
| - | Generic High Entropy Secret | 34d114b | docs/examples/annotation_database_backup_and_sql_parser.ipynb | View secret |
| - | Generic High Entropy Secret | 34d114b | docs/examples/semantic_segmentation_color_thresholding_approach.ipynb | View secret |
| - | Generic High Entropy Secret | 34d114b | docs/examples/creating_gallery_images_review.ipynb | View secret |
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All CI tests are passed except the gitGuardian. Some other .ipynb files are reported as exposing secrets |
They are false positives. |
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Thanks. |
* draft tutorial * added code to the tutorial * added file locations to the notebook. * updated tutorial.
This is the second tutorial that provides information about creating nuclei classifiers. It uses the feature file from the CLI, K-means, and Random forest to build a basic classifier for testing.