{"id":14958295,"url":"https://github.com/alex-lekov/automl_alex","last_synced_at":"2025-04-05T04:09:00.098Z","repository":{"id":43491136,"uuid":"262502731","full_name":"Alex-Lekov/AutoML_Alex","owner":"Alex-Lekov","description":"State-of-the art Automated Machine Learning python library for Tabular Data","archived":false,"fork":false,"pushed_at":"2023-10-04T01:15:37.000Z","size":27179,"stargazers_count":229,"open_issues_count":2,"forks_count":43,"subscribers_count":7,"default_branch":"master","last_synced_at":"2025-04-05T04:07:57.310Z","etag":null,"topics":["auto-ml","automatic-machine-learning","automl","cross-validation","data-science","data-science-projects","hyperparameter-optimization","hyperparameter-tuning","machine-learning","machine-learning-library","machine-learning-models","ml","model-selection","optimisation","python","sklearn","stacking","stacking-ensemble","xgboost"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Alex-Lekov.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2020-05-09T06:14:20.000Z","updated_at":"2025-03-24T01:22:49.000Z","dependencies_parsed_at":"2024-01-15T03:41:44.916Z","dependency_job_id":null,"html_url":"https://github.com/Alex-Lekov/AutoML_Alex","commit_stats":{"total_commits":130,"total_committers":7,"mean_commits":"18.571428571428573","dds":0.5692307692307692,"last_synced_commit":"e6921e491b911406ef58793ef6c352bc91023257"},"previous_names":[],"tags_count":17,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Alex-Lekov%2FAutoML_Alex","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Alex-Lekov%2FAutoML_Alex/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Alex-Lekov%2FAutoML_Alex/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Alex-Lekov%2FAutoML_Alex/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Alex-Lekov","download_url":"https://codeload.github.com/Alex-Lekov/AutoML_Alex/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247284948,"owners_count":20913704,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["auto-ml","automatic-machine-learning","automl","cross-validation","data-science","data-science-projects","hyperparameter-optimization","hyperparameter-tuning","machine-learning","machine-learning-library","machine-learning-models","ml","model-selection","optimisation","python","sklearn","stacking","stacking-ensemble","xgboost"],"created_at":"2024-09-24T13:16:41.726Z","updated_at":"2025-04-05T04:09:00.019Z","avatar_url":"https://github.com/Alex-Lekov.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\r\n\r\n\u003ch3 align=\"center\"\u003eAutoML Alex\u003c/h3\u003e\r\n\r\n\u003cdiv align=\"center\"\u003e\r\n\r\n[![Downloads](https://pepy.tech/badge/automl-alex)](https://pepy.tech/project/automl-alex)\r\n![PyPI - Python Version](https://img.shields.io/pypi/pyversions/automl-alex)\r\n![PyPI](https://img.shields.io/pypi/v/automl-alex)\r\n[![CodeFactor](https://www.codefactor.io/repository/github/alex-lekov/automl_alex/badge)](https://www.codefactor.io/repository/github/alex-lekov/automl_alex)\r\n[![Telegram](https://img.shields.io/badge/chat-on%20Telegram-2ba2d9.svg)](https://t.me/automlalex)\r\n[![License](https://img.shields.io/badge/license-MIT-blue.svg)](/LICENSE)\r\n\r\n\u003c/div\u003e\r\n\r\n---\r\n\r\n\u003cp align=\"center\"\u003e State-of-the art Automated Machine Learning python library for Tabular Data\u003c/p\u003e\r\n\r\n## Works with Tasks:\r\n\r\n-   [x] Binary Classification\r\n\r\n-   [x] Regression\r\n\r\n-   [ ] Multiclass Classification (in progress...)\r\n\r\n### Benchmark Results\r\n\u003cimg width=800 src=\"https://github.com/Alex-Lekov/AutoML-Benchmark/blob/master/img/Total_SUM.png\" alt=\"bench\"\u003e\r\n\r\nThe bigger, the better   \r\nFrom [AutoML-Benchmark](https://github.com/Alex-Lekov/AutoML-Benchmark/) \r\n\r\n### Scheme\r\n\u003cimg width=800 src=\"https://github.com/Alex-Lekov/AutoML_Alex/blob/develop/examples/img/shema.png\" alt=\"scheme\"\u003e\r\n\r\n\r\n# Features\r\n\r\n- Automated Data Clean (Auto Clean)\r\n- Automated **Feature Engineering** (Auto FE)\r\n- Smart Hyperparameter Optimization (HPO)\r\n- Feature Generation\r\n- Feature Selection\r\n- Models Selection\r\n- Cross Validation\r\n- Optimization Timelimit and EarlyStoping\r\n- Save and Load (Predict new data)\r\n\r\n\r\n# Installation\r\n\r\n```python\r\npip install automl-alex\r\n```\r\n\r\n# Docs\r\n[DocPage](https://alex-lekov.github.io/AutoML_Alex/)\r\n\r\n# 🚀 Examples\r\n\r\nClassifier:\r\n```python\r\nfrom automl_alex import AutoMLClassifier\r\n\r\nmodel = AutoMLClassifier()\r\nmodel.fit(X_train, y_train, timeout=600)\r\npredicts = model.predict(X_test)\r\n```\r\n\r\nRegression:\r\n```python\r\nfrom automl_alex import AutoMLRegressor\r\n\r\nmodel = AutoMLRegressor()\r\nmodel.fit(X_train, y_train, timeout=600)\r\npredicts = model.predict(X_test)\r\n```\r\n\r\nDataPrepare:\r\n```python\r\nfrom automl_alex import DataPrepare\r\n\r\nde = DataPrepare()\r\nX_train = de.fit_transform(X_train)\r\nX_test = de.transform(X_test)\r\n```\r\n\r\nSimple Models Wrapper:\r\n```python\r\nfrom automl_alex import LightGBMClassifier\r\n\r\nmodel = LightGBMClassifier()\r\nmodel.fit(X_train, y_train)\r\npredicts = model.predict_proba(X_test)\r\n\r\nmodel.opt(X_train, y_train,\r\n    timeout=600, # optimization time in seconds,\r\n    )\r\npredicts = model.predict_proba(X_test)\r\n```\r\n\r\nMore examples in the folder ./examples:\r\n\r\n- [01_Quick_Start.ipynb](https://github.com/Alex-Lekov/AutoML_Alex/blob/master/examples/01_Quick_Start.ipynb)  [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/Alex-Lekov/AutoML_Alex/blob/master/examples/01_Quick_Start.ipynb)\r\n- [02_Data_Cleaning_and_Encoding_(DataPrepare).ipynb](https://github.com/Alex-Lekov/AutoML_Alex/blob/master/examples/02_Data_Cleaning_and_Encoding_(DataPrepare).ipynb)  [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/Alex-Lekov/AutoML_Alex/blob/master/examples/02_Data_Cleaning_and_Encoding_(DataPrepare).ipynb)\r\n- [03_Models.ipynb](https://github.com/Alex-Lekov/AutoML_Alex/blob/master/examples/03_Models.ipynb)  [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/Alex-Lekov/AutoML_Alex/blob/master/examples/03_Models.ipynb)\r\n- [04_ModelsReview.ipynb](https://github.com/Alex-Lekov/AutoML_Alex/blob/master/examples/04_ModelsReview.ipynb)  [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/Alex-Lekov/AutoML_Alex/blob/master/examples/04_ModelsReview.ipynb)\r\n- [05_BestSingleModel.ipynb](https://github.com/Alex-Lekov/AutoML_Alex/blob/master/examples/05_BestSingleModel.ipynb)  [![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](http://colab.research.google.com/github/Alex-Lekov/AutoML_Alex/blob/master/examples/05_BestSingleModel.ipynb)\r\n- [Production Docker template](https://github.com/Alex-Lekov/AutoML_Alex/blob/master/examples/prod_sample)\r\n\r\n\r\n\r\n# What's inside\r\n\r\nIt integrates many popular frameworks:\r\n- scikit-learn\r\n- XGBoost\r\n- LightGBM\r\n- CatBoost\r\n- Optuna\r\n- ...\r\n\r\n\r\n# Works with Features\r\n\r\n-   [x] Categorical Features\r\n\r\n-   [x] Numerical Features\r\n\r\n-   [x] Binary Features\r\n\r\n-   [ ] Text\r\n\r\n-   [ ] Datetime\r\n\r\n-   [ ] Timeseries\r\n\r\n-   [ ] Image\r\n\r\n\r\n# Note\r\n\r\n- **With a large dataset, a lot of memory is required!**\r\nLibrary creates many new features. If you have a large dataset with a large number of features (more than 100), you may need a lot of memory.\r\n\r\n\r\n# Realtime Dashboard\r\nWorks with [optuna-dashboard](https://github.com/optuna/optuna-dashboard)\r\n\r\n\u003cimg width=800 src=\"https://github.com/Alex-Lekov/AutoML_Alex/blob/develop/examples/img/dashboard.gif\" alt=\"Dashboard\"\u003e\r\n\r\nRun\r\n```console\r\n$ optuna-dashboard sqlite:///db.sqlite3\r\n```\r\n\r\n# Road Map\r\n\r\n-   [x] Feature Generation\r\n\r\n-   [x] Save/Load and Predict on New Samples\r\n\r\n-   [x] Advanced Logging\r\n\r\n-   [x] Add opt Pruners\r\n\r\n-   [ ] Docs Site\r\n\r\n-   [ ] DL Encoders\r\n\r\n-   [ ] Add More libs (NNs)\r\n\r\n-   [ ] Multiclass Classification\r\n\r\n-   [ ] Build pipelines\r\n\r\n\r\n# Contact\r\n\r\n[Telegram Group](https://t.me/automlalex)\r\n\r\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falex-lekov%2Fautoml_alex","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falex-lekov%2Fautoml_alex","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falex-lekov%2Fautoml_alex/lists"}