{ "info": { "author": "Joshua Edgerton, Esteban Fajardo", "author_email": "ef2451@columbia.edu, jae2154@columbia.edu", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "License :: OSI Approved :: BSD License", "Programming Language :: Python :: 2.7", "Topic :: Scientific/Engineering :: Mathematics", "Topic :: Utilities" ], "description": "CompleteThat (v0.1dev) \n====================\n\nCompleteThat is a python package that solves the low rank matrix completion\nproblem. Given a low rank matrix with partial entries the package solves an\noptimization problem to estimate the missing entries.\n\nMathematically, the package solves a relaxation (using the nuclear norm or the \nFrobenius norm of the objective matrix) of the following problem:\n\n minimize_{X} ||X||\n st. X(i,j) = M(i,j) \\forall (i,j)\\in \\Omega,\n where, M represents the data matrix and \\Omega represents the set of p\n observed entries of M\n\nUsage\n-------\n\n>>> from completethat import MatrixCompletion\n>>> problem = MatrixCompletion(M)\n>>> problem.complete_it(algo_name)\n>>> X = problem.get_matrix()\n>>> out_info = problem.get_out() \n\n>>> from completethat import MatrixCompletionBD\n>>> problem = MatrixCompletionBD('input_data.txt')\n>>> problem.train_sgd(dimension=6,init_step_size=.01,min_step=.000001, reltol=.001,rand_init_scale=10, maxiter=1000,batch_size_sgd=50000,shuffle=True)\n>>> problem.validate_sgd('test_data.txt')\n>>> problem.save_model()\n\nAuthors \n-------\n\nThis package was written by Joshua Edgerton and Esteban Fajardo\n\nAcknowledgments\n-------\n\nThis package is the result of the final project for the class EEOR E4650: Convex\nOptimization at Columbia University, Fall 2014. We would like to thank the\nauthors of the different algorithms used in the package to solve the problem.", "description_content_type": null, "docs_url": null, "download_url": "UNKNOWN", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "UNKNOWN", "keywords": null, "license": "BSD", "maintainer": null, "maintainer_email": null, "name": "completethat", "package_url": "https://pypi.org/project/completethat/", "platform": "UNKNOWN", "project_url": "https://pypi.org/project/completethat/", "project_urls": { "Download": "UNKNOWN", "Homepage": "UNKNOWN" }, "release_url": "https://pypi.org/project/completethat/0.1dev/", "requires_dist": null, "requires_python": null, "summary": "A package to solve low rank matrix completion problems", "version": "0.1dev" }, "last_serial": 1391198, "releases": { "0.1dev": [ { "comment_text": "", "digests": { "md5": "ca90c31f7b624deaac512e5d9ebd63ea", "sha256": "a25c55221f5f0df4b5b30a4542e133906fc330e0ee8344c972efa291a970fc58" }, "downloads": -1, "filename": "completethat-0.1dev.tar.gz", "has_sig": false, "md5_digest": "ca90c31f7b624deaac512e5d9ebd63ea", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 5883, "upload_time": "2015-01-04T19:15:03", "url": "https://files.pythonhosted.org/packages/f7/2b/6db22e33ce48ac60fdc1595fdbd0e7401093a8ba3192f756b7767a755b12/completethat-0.1dev.tar.gz" } ] }, "urls": [ { "comment_text": "", "digests": { "md5": "ca90c31f7b624deaac512e5d9ebd63ea", "sha256": "a25c55221f5f0df4b5b30a4542e133906fc330e0ee8344c972efa291a970fc58" }, "downloads": -1, "filename": "completethat-0.1dev.tar.gz", "has_sig": false, "md5_digest": "ca90c31f7b624deaac512e5d9ebd63ea", "packagetype": "sdist", "python_version": "source", "requires_python": null, "size": 5883, "upload_time": "2015-01-04T19:15:03", "url": "https://files.pythonhosted.org/packages/f7/2b/6db22e33ce48ac60fdc1595fdbd0e7401093a8ba3192f756b7767a755b12/completethat-0.1dev.tar.gz" } ] }