{ "info": { "author": "Mayur Shende, Neeraj Bokde", "author_email": "mayur.k.shende@gmail.com, neerajdhanraj@gmail.com", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: MIT License", "Operating System :: OS Independent", "Programming Language :: Python :: 3" ], "description": "# PSF\nPackage: PSF\n\nTitle: Forecasting of univariate time series using the Pattern Sequence-based Forecasting (PSF) algorithm\n\nVersion: 0.1\n\nDate: 9/4/2019\n\nAuthor: Mayur Shende, Neeraj Bokde\n\nMaintainer: Mayur Shende , Neeraj Bokde \n\nDescription: Pattern Sequence Based Forecasting (PSF) takes univariate\n time series data as input and assist to forecast its future values.\n This algorithm forecasts the behavior of time series\n based on similarity of pattern sequences. Initially, clustering is done with the\n labeling of samples from database. The labels associated with samples are then\n used for forecasting the future behaviour of time series data.\n\nLicense: GPL (>= 2)\n\nImports: pandas, numpy, sklearn, matplotlib, warnings, re\n\nPackaged: 2019-04-13 17:15:59 UTC", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/Mayur1009/PSF_py", "keywords": "", "license": "GPL", "maintainer": "", "maintainer_email": "", "name": "PSF-Py", "package_url": "https://pypi.org/project/PSF-Py/", "platform": "", "project_url": "https://pypi.org/project/PSF-Py/", "project_urls": { "Homepage": "https://github.com/Mayur1009/PSF_py" }, "release_url": "https://pypi.org/project/PSF-Py/0.2/", "requires_dist": null, "requires_python": "", "summary": "PSF_Py: Pattern Sequence-based Forecasting (PSF_Py) algorithm", "version": "0.2" }, "last_serial": 5138675, "releases": { "0.2": [ { "comment_text": "", "digests": { "md5": "2639101d7501baa5ac14d82ac06ac7a1", "sha256": "df56ab3e4ce4515dd43d55afe13750e58d9f844fb23456f51570e80dc0d0de34" }, "downloads": -1, "filename": "PSF_Py-0.2.tar.gz", "has_sig": false, "md5_digest": "2639101d7501baa5ac14d82ac06ac7a1", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4992, "upload_time": "2019-04-13T17:17:51", "url": "https://files.pythonhosted.org/packages/22/d2/394d4abefa48038c9aec4881429cfcab062fc5df8f3da347feafe94300c1/PSF_Py-0.2.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "2639101d7501baa5ac14d82ac06ac7a1", "sha256": "df56ab3e4ce4515dd43d55afe13750e58d9f844fb23456f51570e80dc0d0de34" }, "downloads": -1, "filename": "PSF_Py-0.2.tar.gz", "has_sig": false, "md5_digest": "2639101d7501baa5ac14d82ac06ac7a1", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4992, "upload_time": "2019-04-13T17:17:51", "url": "https://files.pythonhosted.org/packages/22/d2/394d4abefa48038c9aec4881429cfcab062fc5df8f3da347feafe94300c1/PSF_Py-0.2.tar.gz" } ] }