Hypernets
A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.
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- hypernets.tabular.evaluator.rst
- hypernets.tabular.feature_generators.rst
- hypernets.tabular.lifelong_learning.rst
- hypernets.tabular.rst
- hypernets.utils.rst
- index.rst
- modules.rst
- nas.md
- overview.md
- quick_start.md
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- Makefile
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- __init__.py
- _configuration.py
- __init__.py
- callbacks.py
- config.py
- context.py
- dispatcher.py
- meta_learner.py
- mutables.py
- objective.py
- ops.py
- pareto.py
- random_state.py
- search_space.py
- searcher.py
- stateful.py
- trial.py
- __init__.py
- _base.py
- percentile.py
- __init__.py
- readme.txt
- spec.proto
- spec_pb2.py
- spec_pb2_grpc.py
- __init__.py
- search_driver_client.py
- search_driver_service.py
- __init__.py
- cluster.py
- driver_dispatcher.py
- executor_dispatcher.py
- __init__.py
- dask_dispatcher.py
- __init__.py
- predict.proto
- predict_pb2.py
- predict_pb2_grpc.py
- readme.txt
- __init__.py
- predict_client.py
- predict_service.py
- __init__.py
- predict_helper.py
- __init__.py
- proc.proto
- proc_pb2.py
- proc_pb2_grpc.py
- readme.txt
- __init__.py
- process_broker_client.py
- process_broker_service.py
- __init__.py
- grpc_process.py
- local_process.py
- ssh_process.py
- __init__.py
- cfg.py
- in_process_dispatcher.py
- run.py
- run_broker.py
- run_predict.py
- run_predict_server.py
- 71.experiment_visualization.ipynb
- __init__.py
- plain_model.py
- smoke_testing.py
- __init__.py
- _callback.py
- _experiment.py
- _extractor.py
- _maker.py
- cfg.py
- compete.py
- general.py
- job.py
- report.py
- __init__.py
- api.py
- appliation.py
- batch.py
- callbacks.py
- cli.py
- consts.py
- executor.py
- scheduler.py
- server.py
- utils.py
- __init__.py
- estimator.py
- hyper_model.py
- objectives.py
- __init__.py
- base.py
- transformers.py
- __init__.py
- evolution_searcher.py
- genetic.py
- grid_searcher.py
- mcts_core.py
- mcts_searcher.py
- moead_searcher.py
- moo.py
- nsga_searcher.py
- playback_searcher.py
- random_searcher.py
- __init__.py
- __init__.py
- _data_cleaner.py
- _data_hasher.py
- _dataframe_mapper.py
- _drift_detection.py
- _ensemble.py
- _estimator.py
- _estimator_detector.py
- _metrics.py
- _model_selection.py
- _persistence.py
- _pseudo_labeling.py
- _toolbox.py
- _transformer.py
- __init__.py
- _collinearity.py
- _data_cleaner.py
- _data_hasher.py
- _dataframe_mapper.py
- _drift_detection.py
- _ensemble.py
- _feature_generators.py
- _metrics.py
- _model_selection.py
- _persistence.py
- _pseudo_labeling.py
- _toolbox.py
- _transformers.py
- __init__.py
- adult-uci.csv.gz
- bank-uci.csv.gz
- Bike_Sharing.csv
- blood.csv
- boston.csv.gz
- dsutils.py
- glass_uci.csv
- heart-disease-uci.csv
- movielens_sample.txt
- telescope.csv
- __init__.py
- base_ensemble.py
- misc.py
- stacking.py
- voting.py
- __init__.py
- _base.py
- auto_sklearn.py
- h2o.py
- hyperdt.py
- hypergbm.py
- tests.py
- tpot.py
- __init__.py
- _base.py
- _primitives.py
- _transformers.py
- __init__.py
- _split.py
- _validation.py
- __init__.py
- _base.py
- cache.py
- cfg.py
- collinearity.py
- column_selector.py
- data_cleaner.py
- data_hasher.py
- dataframe_mapper.py
- drift_detection.py
- estimator_detector.py
- metrics.py
- persistence.py
- pseudo_labeling.py
- sklearn_ex.py
- toolbox.py
- __init__.py
- __init__.py
- callback_test.py
- connection_space_test.py
- hyper_space_test.py
- mutable_test.py
- parameter_test.py
- __init__.py
- base_test.py
- percentile.py
- __init__.py
- process_test.py
- __init__.py
- compete_experiment_test.py
- experiment_factory.py
- extractor_test.py
- general_experiment_test.py
- job_test.py
- make_experiment_test.py
- report_test.py
- run_export_experiment_report.py
- __init__.py
- batch_factory.py
- job_template.yml
- local_batch.json
- minimum_batch.json
- plain_job_script.py
- remote_batch.json
- test_application.py
- test_batch.py
- test_cli.py
- test_scheduler.py
- __init__.py
- plain_model_test.py
- test_objectives.py
- __init__.py
- pipeline_test.py
- __init__.py
- evolution_test.py
- grid_test.py
- mcts_test.py
- playback_test.py
- random_test.py
- test_genetic.py
- test_moead_searcher.py
- test_moo.py
- test_nsga2_searcher.py
- __init__.py
- ensemble_test.py
- __init__.py
- split_test.py
- __init__.py
- cache_test.py
- data_cleaner_test.py
- data_split_test.py
- drift_detection_test.py
- estimator_test.py
- experiment_test.py
- feature_importance_test.py
- psudo_labeling_test.py
- toolbox_test.py
- transformer_test.py
- __init__.py
- cache_test.py
- dask_ex_test.py
- dask_transofromer_test.py
- data_cleaner_test.py
- drift_detection_test.py
- feature_generator_dask_test.py
- feature_importance_test.py
- persitence_test.py
- psudo_labeling_test.py
- toolbox_test.py
- __init__.py
- cache_test.py
- column_selector_test.py
- data_cleaner_test.py
- drift_detection_test.py
- feature_generator_test.py
- feature_importance_test.py
- persitence_test.py
- psudo_labeling_test.py
- sklearn_transformer_test.py
- toolbox_test.py
- utils_test.py
- __init__.py
- trial_history_test.py
- trial_store_test.py
- __init__.py
- common_test.py
- df_utils_test.py
- estimators_test.py
- perf_test.py
- ssh_utils_test.py
- tic_toc_test.py
- tuning_test.py
- __init__.py
- __init__.py
- _doc_lens.py
- _estimators.py
- _fsutils.py
- _perf.py
- _tic_tok.py
- common.py
- const.py
- df_utils.py
- logging.py
- param_tuning.py
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- __init__.py
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- requirements-board.txt
- requirements-cuml.txt
- requirements-dask.txt
- requirements-extra.txt
- requirements-fg.txt
- requirements-notebook.txt
- requirements-tests.txt
- requirements-zhcn.txt
- requirements.txt
- setup.cfg
- setup.py
# Installation Guide
1. Get the code
git clone https://github.com/DataCanvasIO/Hypernets
Downloads the entire project code from GitHub to your computer.
cd Hypernets
Moves into the project folder you just downloaded.
2. Official Install Script
Easy RecommendedPrerequisites
- Python 3 Python is required to use pip.
pip install hypernets
Installs the package published on PyPI directly β no need to clone the source.
pip install hypernets[notebook]
Installs the package published on PyPI directly β no need to clone the source.
pip install hypernets[dask]
Installs the package published on PyPI directly β no need to clone the source.
pip install hypernets[zhcn]
Installs the package published on PyPI directly β no need to clone the source.
After installing, open a new terminal and run the program's version command (e.g. --version) to confirm it worked.
Pulled directly from this repo's README.
3. Python
EasyPrerequisites
pip install hypernets
Installs the package published on PyPI directly β no need to clone the source.
pip install hypernets[notebook]
Installs the package published on PyPI directly β no need to clone the source.
pip install hypernets[dask]
Installs the package published on PyPI directly β no need to clone the source.
pip install hypernets[zhcn]
Installs the package published on PyPI directly β no need to clone the source.
pip install hypernets[all]
Installs the package published on PyPI directly β no need to clone the source.
If it runs without errors and prints output in the terminal, it worked.
Pulled directly from this repo's README.
// repository documentation
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