{ "info": { "author": "Shinya SUZUKI", "author_email": "shinya.s.825@gmail.com", "bugtrack_url": null, "classifiers": [ "License :: OSI Approved :: MIT License", "Programming Language :: Python", "Programming Language :: Python :: 3", "Topic :: Scientific/Engineering :: Information Analysis" ], "description": "|Build Status|\n\nHMC-loss\n========\n\nAbstruct\n--------\n\nPython-implemented hierarchical multi-class validation metrics: HMC-loss\n. Original paper is `(Bi&Kwok,\n2012) `__ .\n\nInstall\n-------\n\n::\n\n pip install hmc_loss\n\nRequirement\n-----------\n\n- numpy\n- Network X\n\nHow to use\n----------\n\nThis metrics is implemented like scikit-learn metrics.\n\n::\n\n from hmc_loss import hmc_loss_score, get_cost_list\n import numpy as np\n\n # Generate label data(2-D array of numpy)\n true_label = np.random.randint(2, size(100, 100))\n pred_label = np.random.randint(2, size(100, 100))\n\n # Generate test graph(Di-Graph of NetworkX)\n graph = nx.gnc_graph(100)\n # Generate element list of graph node\n label_list = list(range(100))\n # Calculate cost of each node in graph\n cost_list = get_cost_list(graph, 0, label_list)\n # Calculate HMC-loss\n hmc_loss_score(true_label, pred_label, graph, 0, label_list, cost_list, alpha=0.5, beta=1.5)\n\nLicence\n-------\n\n`MIT `__\n\nAuthor\n------\n\n`Taske HAMANO `__\n\n.. |Build Status| image:: https://travis-ci.org/TaskeHAMANO/hmc_loss.svg?branch=master\n :target: https://travis-ci.org/TaskeHAMANO/hmc_loss\n", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/TaskeHAMANO/hmc_loss", "keywords": "validation", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "hmc_loss", "package_url": "https://pypi.org/project/hmc_loss/", "platform": "", "project_url": "https://pypi.org/project/hmc_loss/", "project_urls": { "Homepage": "https://github.com/TaskeHAMANO/hmc_loss" }, "release_url": "https://pypi.org/project/hmc_loss/1.0.0/", "requires_dist": null, "requires_python": "", "summary": "", "version": "1.0.0" }, "last_serial": 2825146, "releases": { "0.1.0": [ { "comment_text": "", "digests": { "md5": "a8d6f07e21071d7c9a9e40605d3d037f", "sha256": "243352db14b129db501595f3aaab28f9900e670ecd90d9e84d812280958f6f6a" }, "downloads": -1, "filename": "hmc_loss-0.1.0.tar.gz", "has_sig": false, "md5_digest": "a8d6f07e21071d7c9a9e40605d3d037f", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4032, "upload_time": "2016-06-23T05:50:23", "url": "https://files.pythonhosted.org/packages/79/ad/6be577463a1b97b1eca13813ca6070807d128d64bb5e3fc48203ebda0d12/hmc_loss-0.1.0.tar.gz" } ], "0.2.0": [ { "comment_text": "", "digests": { "md5": "110f15ece87fda0982eb8d248ac8dff2", "sha256": "672c6d96a8931658af5e69ae32fdfc8bb67ae585152cfc1f342bbee8ca14ff53" }, "downloads": -1, "filename": "hmc_loss-0.2.0.tar.gz", "has_sig": false, "md5_digest": "110f15ece87fda0982eb8d248ac8dff2", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4749, "upload_time": "2016-06-23T10:07:42", "url": "https://files.pythonhosted.org/packages/95/f8/2325731c872409731baa407bd37f3cd122b5847377c4b94ec9a9a592139d/hmc_loss-0.2.0.tar.gz" } ], "0.3.0": [ { "comment_text": "", "digests": { "md5": "24cef064cdad3d9882c28cb3ced1385a", "sha256": "a163bc813c8e92a94c095b28aab869aa28488c588bb0fb9d89187ec9d87e80f5" }, "downloads": -1, "filename": "hmc_loss-0.3.0.tar.gz", "has_sig": false, "md5_digest": "24cef064cdad3d9882c28cb3ced1385a", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4809, "upload_time": "2016-06-28T06:16:54", "url": "https://files.pythonhosted.org/packages/8d/eb/399d70488ca4545bc2434cf8194990ae228e86c132032efc69851ee624ff/hmc_loss-0.3.0.tar.gz" } ], "0.3.1": [ { "comment_text": "", "digests": { "md5": "42cc8b219f97e93a0b6f01b0bf8ea900", "sha256": "7d587a0bb065daf5294dc81c3d90d379ab87847b1315dd980054ae5fbb8a707b" }, "downloads": -1, "filename": "hmc_loss-0.3.1.tar.gz", "has_sig": false, "md5_digest": "42cc8b219f97e93a0b6f01b0bf8ea900", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 4810, "upload_time": "2016-06-28T09:52:07", "url": "https://files.pythonhosted.org/packages/18/50/26c1383b1db7cc6323e52b8c720c315bbc76ef29c140a3e38c45ebc5822f/hmc_loss-0.3.1.tar.gz" } ], "0.4.0": [ { "comment_text": "", "digests": { "md5": "13ddeedb0e54ada325a612ad48d93ec3", "sha256": "8f7d6c959249368d4dea45991f6079aceea2cb8fc609b12b664b427a908dc9e9" }, "downloads": -1, "filename": "hmc_loss-0.4.0.tar.gz", "has_sig": false, "md5_digest": "13ddeedb0e54ada325a612ad48d93ec3", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 5128, "upload_time": "2016-06-29T08:14:51", "url": "https://files.pythonhosted.org/packages/4e/25/d741629eb7dd632fc675c47b13428e8ec7d672d7837c141fd27241904580/hmc_loss-0.4.0.tar.gz" } ], "1.0.0": [ { "comment_text": "", "digests": { "md5": "7880a030f789d706788fc95100f958a9", "sha256": "3d454b6d715eaf37268340ba5a55b384b42d4bebf923c5433361c585eb0649dc" }, "downloads": -1, "filename": "hmc_loss-1.0.0.tar.gz", "has_sig": false, "md5_digest": "7880a030f789d706788fc95100f958a9", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 3657, "upload_time": "2017-04-24T08:21:10", "url": "https://files.pythonhosted.org/packages/44/16/d8cd51d8ef7f4a6212ef699d243dbfe83222dd7d22eec440f27b4d164305/hmc_loss-1.0.0.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "7880a030f789d706788fc95100f958a9", "sha256": "3d454b6d715eaf37268340ba5a55b384b42d4bebf923c5433361c585eb0649dc" }, "downloads": -1, "filename": "hmc_loss-1.0.0.tar.gz", "has_sig": false, "md5_digest": "7880a030f789d706788fc95100f958a9", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 3657, "upload_time": "2017-04-24T08:21:10", "url": "https://files.pythonhosted.org/packages/44/16/d8cd51d8ef7f4a6212ef699d243dbfe83222dd7d22eec440f27b4d164305/hmc_loss-1.0.0.tar.gz" } ] }