LightAutoML
Fast and customizable framework for automatic ML model creation (AutoML)
File Explorer
- bug_report.md
- config.yml
- feature_request.md
- question.md
- CI.yml
- docs.yml
- mirror.yml
- publish_pypi.yml
- tests_macos.yml
- tests_ubuntu.yml
- tests_windows.yml
- CONTRIBUTING.md
- .gitlab-ci.yml
- release.yml
- jupyter_notebook_config.py
- style.css
- class.rst
- module.rst
- classtemplate.rst
- functiontemplate.rst
- addons.rst
- automl.rst
- dataset.rst
- image.rst
- ml_algo.rst
- ml_algo.torch_based.rst
- ml_algo.tuning.rst
- pipelines.features.rst
- pipelines.ml.rst
- pipelines.rst
- pipelines.selection.rst
- reader.rst
- report.rst
- tasks.losses.rst
- tasks.rst
- text.rst
- transformers.rst
- utils.rst
- validation.rst
- Tutorial_10_relational_data_with_star_scheme.nblink
- Tutorial_11_time_series.nblink
- Tutorial_12_AA_Test.nblink
- Tutorial_13_AA_Test_multigroup_split.nblink
- Tutorial_14_AB_Test.nblink
- Tutorial_15_Matching.nblink
- Tutorial_16_Matching_without_replacement.nblink
- Tutorial_17_Modeling_Limit_Distribution.nblink
- Tutorial_18_Test_Limit_Distribution.nblink
- Tutorial_1_basics.nblink
- Tutorial_2_WhiteBox_AutoWoE.nblink
- Tutorial_3_sql_data_source.nblink
- Tutorial_4_NLP_Interpretation.nblink
- Tutorial_5_uplift.nblink
- Tutorial_6_custom_pipeline.nblink
- Tutorial_7_ICE_and_PDP_interpretation.nblink
- Tutorial_8_CV_preset.nblink
- Tutorial_9_neural_networks.nblink
- Installation.rst
- Kaggle_Kernels.rst
- Others.rst
- Python-API.rst
- Tutorials.rst
- conf.py
- index.rst
- Makefile
- mock_docs.py
- requirements.txt
- fulfilment_center_info.csv
- meal_info.csv
- relational_main.csv.zip
- ai92_value_77.csv
- avito1k_train.csv
- jobs_train.csv
- sampled_app_train.csv
- ts_data.csv
- conditional_parameters.py
- custom_search_space.py
- sequential_parameter_search.py
- Tutorial_10_relational_data_with_star_scheme.ipynb
- Tutorial_11_time_series.ipynb
- Tutorial_12_AA_Test.ipynb
- Tutorial_13_AA_Test_multigroup_split.ipynb
- Tutorial_14_AB_Test.ipynb
- Tutorial_15_Matching.ipynb
- Tutorial_16_Matching_without_replacement.ipynb
- Tutorial_17_Modeling_Limit_Distribution.ipynb
- Tutorial_18_Test_Limit_Distribution.ipynb
- Tutorial_1_basics.ipynb
- Tutorial_2_WhiteBox_AutoWoE.ipynb
- Tutorial_3_sql_data_source.ipynb
- Tutorial_4_NLP_Interpretation.ipynb
- Tutorial_5_uplift.ipynb
- Tutorial_6_custom_pipeline.ipynb
- Tutorial_7_ICE_and_PDP_interpretation.ipynb
- Tutorial_8_CV_preset.ipynb
- Tutorial_9_neural_networks.ipynb
- demo0.py
- demo1.py
- demo10.py
- demo11.py
- demo12.py
- demo13.py
- demo14.py
- demo15.py
- demo2.py
- demo3.py
- demo4.py
- demo5.py
- demo6.py
- demo7.py
- demo8.py
- demo9.py
- README.md
- simple_tabular_classification.py
- autoint.png
- denselight.png
- densenet.png
- fttransformer.png
- GENERALL2X2.jpg
- lightautoml_icon_color.png
- LightAutoML_logo_big.png
- lightautoml_logo_color.png
- LightAutoML_logo_small.png
- lime.jpg
- node.png
- resnet.png
- Star_scheme_tables.png
- swa.png
- TabularAutoML_model_descr.png
- TabularUtilizedAutoML_model_descr.png
- tutorial_11_case_problem_statement.png
- tutorial_11_general_problem_statement.png
- tutorial_11_history_step_params.png
- tutorial_11_transformers_params.png
- tutorial_1_initial_report.png
- tutorial_1_laml_big.png
- tutorial_1_ml_pipeline.png
- tutorial_1_pipeline.png
- tutorial_1_unfolded_report.png
- tutorial_2_initial_report.png
- tutorial_2_pipeline.png
- tutorial_2_unfolded_report.png
- tutorial_3_initial_report.png
- tutorial_3_unfolded_report.png
- tutorial_blackbox_pipeline.png
- tutorial_whitebox_report_1.png
- tutorial_whitebox_report_2.png
- tutorial_whitebox_report_3.png
- tutorial_whitebox_report_4.png
- base.py
- __init__.py
- __init__.py
- data_process.py
- l2x.py
- l2x_model.py
- lime.py
- utils.py
- __init__.py
- sswarm.py
- __init__.py
- base.py
- metalearners.py
- metrics.py
- utils.py
- __init__.py
- utilization.py
- __init__.py
- conf_0_sel_type_0.yml
- conf_1_sel_type_1.yml
- conf_2_select_mode_1_no_typ.yml
- conf_3_sel_type_1_no_inter_lgbm.yml
- conf_4_sel_type_0_no_int.yml
- conf_5_sel_type_1_tuning_full.yml
- conf_6_sel_type_1_tuning_full_no_int_lgbm.yml
- __init__.py
- base.py
- image_config.yml
- image_presets.py
- tabular_config.yml
- tabular_presets.py
- text_config.yml
- text_presets.py
- time_series_config.yml
- utils.py
- whitebox_config.yml
- whitebox_presets.py
- __init__.py
- base.py
- blend.py
- __init__.py
- base.py
- np_pd_dataset.py
- roles.py
- seq_np_pd_dataset.py
- utils.py
- __init__.py
- image.py
- utils.py
- utils.py
- autoint_utils.py
- ghost_norm.py
- fttransformer_utils.py
- sampler.py
- __init__.py
- linear_model.py
- nn_models.py
- node_nn_model.py
- __init__.py
- base.py
- hyperopt.py
- optuna.py
- __init__.py
- base.py
- boost_cb.py
- boost_lgbm.py
- boost_xgb.py
- dl_model.py
- icl.py
- linear_sklearn.py
- random_forest.py
- utils.py
- whitebox.py
- __init__.py
- base.py
- generator_pipeline.py
- image_pipeline.py
- lgb_pipeline.py
- linear_pipeline.py
- text_pipeline.py
- torch_pipeline.py
- wb_pipeline.py
- __init__.py
- base.py
- nested_ml_pipe.py
- whitebox_ml_pipe.py
- __init__.py
- base.py
- importance_based.py
- linear_selector.py
- permutation_importance_based.py
- __init__.py
- utils.py
- __init__.py
- base.py
- guess_roles.py
- seq.py
- tabular_batch_generator.py
- utils.py
- binary_inference_section.html
- feature_importance_section.html
- feature_importance_utillized_section.html
- interpretation_section.html
- interpretation_subsection.html
- lama_base_template.html
- model_section.html
- model_section_utilized.html
- multiclass_inference_section.html
- nlp_section.html
- nlp_subsection.html
- preset_section.html
- reg_inference_section.html
- results_section.html
- train_set_section.html
- train_set_section_utilized.html
- uplift_section.html
- uplift_subsection.html
- utilized_data_subsections.html
- whitebox_section.html
- __init__.py
- report_deco.py
- __init__.py
- base.py
- cb.py
- cb_custom.py
- lgb.py
- lgb_custom.py
- sklearn.py
- torch.py
- xgb.py
- __init__.py
- base.py
- common_metric.py
- utils.py
- __init__.py
- dl_transformers.py
- dp_utils.py
- embed.py
- embed_dataset.py
- nn_model.py
- tokenizer.py
- trainer.py
- utils.py
- weighted_average_transformer.py
- __init__.py
- base.py
- categorical.py
- composite.py
- datetime.py
- decomposition.py
- generator.py
- groupby.py
- image.py
- numeric.py
- seq.py
- text.py
- utils.py
- __init__.py
- installation.py
- logging.py
- timer.py
- __init__.py
- base.py
- np_iterators.py
- utils.py
- __init__.py
- run.py
- run_tabular.py
- utils.py
- exp_branch_push.py
- poetry_fix.py
- README.md
- run_tutorials.py
- integration_utils.py
- test_custom_2_level_stacking.py
- test_demo0.py
- test_demo1.py
- test_demo10.py
- test_demo11.py
- test_demo12.py
- test_demo13.py
- test_demo15.py
- test_demo2.py
- test_demo3.py
- test_demo4.py
- test_demo5.py
- test_demo6.py
- test_demo7.py
- test_demo8.py
- __init__.py
- __init__.py
- presets_utils.py
- test_tabularautoml.py
- test_tabularautoml_nn.py
- test_tabularautoml_tabicl.py
- test_tabularautoml_tabm.py
- test_tabularautoml_xgb.py
- test_tabularnlpautoml.py
- test_tabularutilizedautoml.py
- test_uplift.py
- test_whiteboxpreset.py
- __init__.py
- __init__.py
- __init__.py
- test_optuna_tuner.py
- __init__.py
- __init__.py
- __init__.py
- __init__.py
- __init__.py
- __init__.py
- __init__.py
- test_numeric.py
- __init__.py
- test_logging.py
- __init__.py
- __init__.py
- __init__.py
- conftest.py
- .editorconfig
- .gitignore
- .pre-commit-config.yaml
- .readthedocs.yml
- _config.yml
- check_docs.py
- LICENSE
- pyproject.toml
- README.md
- setup.cfg
- setup.py
- tox.ini
# Use via CDN
jsDelivrjsDelivr serves any public GitHub repository as a CDN with zero setup. Pick a version and a file to get a ready-to-paste link and snippet.
Link
Example
Command Glossary
Commands referenced in this DOCs, explained below.
brew install
View Details ▼
brew install
Install a Homebrew formula or cask.
brew install {{formula|cask}}
Install a formula/cask:
brew install {{[-s|--build-from-source]}} {{formula}}
Build and install a formula from source (dependencies will still be installed from bottles):
brew install {{[-n|--dry-run]}} {{formula|cask}}
Download the manifest, print what would be installed but don't actually install anything:
pip install
View Details ▼
pip install
Install Python packages.
pip install {{package1 package2 ...}}
Install one or more packages:
pip install {{package1 package2 ...}} {{[-U|--upgrade]}}
Upgrade all specified packages to the latest version, installing any that are not already present:
pip install {{package}}=={{version}}
Install a specific version of a package:
python
View Details ▼
python
Python language interpreter.
python
Start a REPL (interactive shell):
python {{path/to/file.py}}
Execute a specific Python file:
python -i {{path/to/file.py}}
Execute a specific Python file and start a REPL:
apt-get
View Details ▼
apt-get
Debian and Ubuntu package management utility.
Search for packages using `apt-cache`.
It is recommended to use `apt` when used interactively in Ubuntu versions 16.04 and later.
sudo apt-get update
Update the list of available packages and versions (it's recommended to run this before other `apt-get` commands):
sudo apt-get install {{package}}
Install a package, or update it to the latest available version:
sudo apt-get remove {{package}}
Remove a package:
yum
View Details ▼
yum
This command is an alias of `dnf` on modern distros.
For older distros (e.g. CentOS 7), `yum` is a distinct program from `dnf`. Some subcommands and options may be different.
tldr dnf
View documentation for the original command:
// repository documentation
Was this content helpful?
(0 ratings)