scikit-learn/examples/applications
Olivier Grisel 84a7a7a802
ENH Specify categorical features with feature names in HGBDT (#24889)
* Allow categorical_features to be passed as feature names

* Update relevant examples

* Call .set_output(transform='pandas') on the pipelines
2022-11-13 13:40:47 +01:00
..
README.txt DOC: Fixed links to modules in the example gallery 2011-12-19 16:07:01 +01:00
plot_cyclical_feature_engineering.py ENH Specify categorical features with feature names in HGBDT (#24889) 2022-11-13 13:40:47 +01:00
plot_digits_denoising.py ENH improve ARFF parser using pandas (#21938) 2022-05-12 18:21:15 +02:00
plot_face_recognition.py MNT Speed up of plot_face_recognition.py example (#21725) 2021-12-15 11:05:48 +01:00
plot_model_complexity_influence.py DOC moved legend to upper center (#24847) 2022-11-07 10:51:21 +01:00
plot_out_of_core_classification.py DOC Check sha256 digests of tarballs in tutorial and examples before extraction (#24617) 2022-10-10 17:57:42 +02:00
plot_outlier_detection_wine.py MAINT consistent use of `print(__doc__)` in examples (#21307) 2021-10-22 15:33:22 +02:00
plot_prediction_latency.py DOC: use notebook-style in plot_prediction_latency.py (#22418) 2022-02-14 07:57:26 +01:00
plot_species_distribution_modeling.py DOC Correct typos in plot_species_distribution_modeling (#24256) 2022-08-24 17:02:10 -04:00
plot_stock_market.py DOC Added links and corrected typos to plot_stock_market.py (#24209) 2022-08-24 15:04:47 +02:00
plot_tomography_l1_reconstruction.py MNT Update black to stable version (#22474) 2022-02-15 11:36:26 +01:00
plot_topics_extraction_with_nmf_lda.py FEA Online implementation of non-negative matrix factorization (#16948) 2022-04-22 17:51:06 +02:00
svm_gui.py MAINT consistent use of `print(__doc__)` in examples (#21307) 2021-10-22 15:33:22 +02:00
wikipedia_principal_eigenvector.py MNT Use context manager for file operations (#23207) 2022-04-29 11:55:55 +02:00

README.txt

.. _realworld_examples:

Examples based on real world datasets
-------------------------------------

Applications to real world problems with some medium sized datasets or
interactive user interface.