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 :alt: PyPI - Downloads\n.. _PyPi: https://pypi.org/project/libsvm/\n\nLibSVM\n======\n\nDescription\n-----------\n\nPre-built LibSVM packages for Python.\n\nWhat is LibSVM?\n---------------\n\nCrated by Chih-Chung Chang and Chih-Jen Lin, LIBSVM is an integrated\nsoftware for support vector classification, (C-SVC, nu-SVC), regression\n(epsilon-SVR, nu-SVR) and distribution estimation (one-class SVM). It\nsupports multi-class classification.\n\nOriginal Links\n--------------\n\n-  Repository: https://github.com/cjlin1/libsvm\n-  Library website: https://www.csie.ntu.edu.tw/~cjlin/libsvm\n\nPurpose of this package\n-----------------------\n\nThe idea behind this package is to use the same code as in\nhttps://github.com/cjlin1/libsvm using the very convenient pip command\n\nHow to install\n--------------\n\n::\n\n   pip install libsvm\n\nExample\n-------\n\n1. Download https://github.com/cjlin1/libsvm/blob/master/heart_scale\n   file.\n2. Run the following commands\n\n::\n\n   \u003e\u003e\u003e from libsvm.svmutil import *\n   \u003e\u003e\u003e y, x = svm_read_problem('path/to/heart_scale')\n   \u003e\u003e\u003e m = svm_train(y[:200], x[:200], '-c 4')\n   *.*\n   optimization finished, #iter = 257\n   nu = 0.351161\n   obj = -225.628984, rho = 0.636110\n   nSV = 91, nBSV = 49\n   Total nSV = 91\n   \u003e\u003e\u003e p_label, p_acc, p_val = svm_predict(y[200:], x[200:], m)\n   Accuracy = 84.2857% (59/70) (classification)\n\nWindows\n-------\n\nThe package contains a pre-built Windows binary that is only compatible with 64 bits architecture; therefore,\n32 bits architecture is not compatible.\n\nCygwin\n______\n\nIn case that you want to install this package using Cygwin, you have to make sure that the\nfollowing packages are installed:\n\n1. gcc-g++ \u003e= 7.0.0\n2. python38\n3. python38-devel\n4. python38-pip\n\nSome good tutorials to install Cygwin packages are the following:\n\n- https://wiki.usask.ca/display/MESH/Running+Python+from+the+Cygwin+Terminal\n- https://www.davidbaumgold.com/tutorials/set-up-python-windows/#installing-cygwin\n\nCopyright\n---------\n\nCopyright (c) 2000-2018 Chih-Chung Chang and Chih-Jen Lin All rights\nreserved.\n\nRedistribution and use in source and binary forms, with or without\nmodification, are permitted provided that the following conditions are\nmet:\n\n1. Redistributions of source code must retain the above copyright\n   notice, this list of conditions and the following disclaimer.\n\n2. Redistributions in binary form must reproduce the above copyright\n   notice, this list of conditions and the following disclaimer in the\n   documentation and/or other materials provided with the distribution.\n\n3. Neither name of copyright holders nor the names of its contributors\n   may be used to endorse or promote products derived from this software\n   without specific prior written permission.\n\nTHIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS\n\"AS IS\" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT\nLIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A\nPARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE REGENTS OR\nCONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,\nEXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,\nPROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR\nPROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF\nLIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING\nNEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS\nSOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.\n\nMaintainer\n----------\n\n-  Ricardo Ocampo `me@ocampor.ai`_\n\n.. _me@ocampor.ai: me@ocampor.ai\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Focampor%2Flibsvm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Focampor%2Flibsvm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Focampor%2Flibsvm/lists"}