{ "info": { "author": "See License.txt file in source package", "author_email": "manuel.castejon@unileon.es", "bugtrack_url": null, "classifiers": [ "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Operating System :: MacOS", "Operating System :: Microsoft :: Windows", "Operating System :: POSIX", "Operating System :: Unix", "Programming Language :: Python :: 3.6", "Topic :: Scientific/Engineering", "Topic :: Software Development" ], "description": "Welcome to PipeGraph!\n============================================\n\nIntroduction\n------------\n\nScikit-Learn's Pipeline is a very useful tool to bind a sequence of transformers and a final estimator\nin a single unit capable of working itself as an estimator. This eases managing the fit and predict\nof the complete sequence of steps through a simple call to their fit and predict methods,\nand in combination with the GridSearchCV function allows to tune the hyperparameters of these steps\nwhile in the search for the best model.\n\nPipeGraph extends the concept of Pipeline by using a graph structure that can handle Scikit-Learn's\nobjects in imaginative layouts. This allows the user to:\n\n- Express simple and complex sequences of steps, from linear workflows to elaborated graphs\n- To have access to all the data generated along the intermediate steps\n- To use GridSearchCV on those graphs\n\nLet's see a few examples to understand how we can express these situations through PipeGraph objects.\n\nLICENSE\n------------\nThe MIT License (MIT)\n\nCopyright (c) 2018 Laura Fernandez Robles,\n Hector Alaiz Moreton,\n Jaime Cifuentes-Rodriguez,\n Javier Alfonso-Cend\u00f3n,\n Camino Fern\u00e1ndez-Llamas,\n Manuel Castej\u00f3n-Limas\n\n\nPermission is hereby granted, free of charge, to any person obtaining a copy\nof this software and associated documentation files (the \"Software\"), to deal\nin the Software without restriction, including without limitation the rights\nto use, copy, modify, merge, publish, distribute, sublicense, and/or sell\ncopies of the Software, and to permit persons to whom the Software is\nfurnished to do so, subject to the following conditions:\n\nThe above copyright notice and this permission notice shall be included in all\ncopies or substantial portions of the Software.\n\nTHE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\nIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\nFITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\nAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\nLIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\nOUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE\nSOFTWARE.\n\n", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://mcasl.github.io/PipeGraph/", "keywords": "scikit-learn pipeline development", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "pipeGraph", "package_url": "https://pypi.org/project/pipeGraph/", "platform": "", "project_url": "https://pypi.org/project/pipeGraph/", "project_urls": { "Homepage": "https://mcasl.github.io/PipeGraph/" }, "release_url": "https://pypi.org/project/pipeGraph/0.3.3/", "requires_dist": [ "pytest", "scikit-learn (>=0.17)", "networkx", "pandas", "check-manifest ; extra == 'dev'", "coverage ; extra == 'test'" ], 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