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PyOnlineSVR\n\n[![pipeline status](https://github.com/CodeLionX/pyonlinesvr/actions/workflows/conda-python-test.yml/badge.svg)](https://github.com/CodeLionX/pyonlinesvr/actions/workflows/conda-python-test.yml)\n![coverage report](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/CodeLionX/6762bee806477c52e079f21d2f252688/raw/pyonlinesvr__heads_main.json)\n[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n[![release info](https://img.shields.io/badge/Release-0.0.3-blue)](https://pypi.org/project/PyOnlineSVR/0.0.3/)\n[![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)\n![python version 3.7|3.8|3.9|3.10](https://img.shields.io/badge/python-3.7%20%7C%203.8%20%7C%203.9%20%7C%203.10-blue)\n\nPython-Wrapper for Francesco Parrella's OnlineSVR [[PAR2007]](#PAR2007) C++ implementation with [scikit-learn](https://sklearn.org/)-compatible interfaces.\nYou can find more information about the OnlineSVR [here](http://onlinesvr.altervista.org/) and the original source code [here](https://github.com/fp2556/onlinesvr/tree/master/c%2B%2B).\n\n## Installation\n\n### Dependencies\n\nPyOnlineSVR requires the following dependencies:\n\n- python (\u003e=3.7)\n- numpy (\u003e=1.13.3)\n- scipy (\u003e=0.19.1)\n- joblib (\u003e=0.11)\n- scikit-learn (\u003e=0.23.0)\n\n### Binaries\n\nPyOnlineSVR is published to [PyPi](https://pypi.org/project/PyOnlineSVR/) and can be installed using `pip`.\n\n#### Prerequisites\n\n- python (\u003e=3.7)\n- pip (\u003e=19.0 to support [manylinux2010](https://github.com/pypa/manylinux))\n\n#### Steps\n\nYou can use `pip` to install PyOnlineSVR using:\n\n```sh\npip install PyOnlineSVR\n```\n\n### From Source (Linux)\n\nIf you are installing PyOnlineSVR from source, you will need Python 3.7 or later and a modern C++ compiler.\nWe highly recommend using an [Anaconda](https://www.anaconda.com/products/individual#download-section) environment for building this project.\n\nIn the following, we explain the steps to build PyOnlineSVR using **Anaconda** and **git**.\n\n#### Prepare environment\n\nCreate a new Anaconda environment and install the required dependencies.\nThis includes python, [SWIG](http://swig.org/) to generate the C++ wrapper, and the C and C++ compiler toolchains.\n\n```bash\nconda create -n pyonlinesvr python swig gcc_linux-64 gxx_linux-64\nconda activate pyonlinesvr\n```\n\n#### Install dependencies\n\n```bash\nconda install -n pyonlinesvr numpy scipy scikit-learn\n```\n\n#### Get the source code\n\n```bash\ngit clone https://github.com/CodeLionX/pyonlinesvr.git\ncd pyonlinesvr\n```\n\n#### Install PyOnlineSVR\n\n```bash\npython setup.py install\n```\n\nNote that if your are using Anaconda, you may experience an error caused by the linker:\n\n```txt\nbuild/temp.linux-x86_64-3.7/torch/csrc/stub.o: file not recognized: file format not recognized\ncollect2: error: ld returned 1 exit status\nerror: command 'g++' failed with exit status 1\n```\n\nThis is caused by the linker `ld` from the Conda environment shadowing the system `ld`.\nYou should use a newer version of Python in your environment that fixes this issue.\nThe recommended Python versions are (3.6.10+,) 3.7.6+ and 3.8.1+.\nFor further details see [the issue](https://github.com/ContinuumIO/anaconda-issues/issues/11152).\n\n## Usage\n\n```python\n\u003e\u003e\u003e import numpy as np\n\u003e\u003e\u003e from pyonlinesvr import OnlineSVR\n\u003e\u003e\u003e X = np.array([[0, 0], [2, 2]])\n\u003e\u003e\u003e y = np.array([0.5, 2.5])\n\u003e\u003e\u003e regr = OnlineSVR()\n\u003e\u003e\u003e regr.fit(X[:1], y[:1])\nOnlineSVR()\n\u003e\u003e\u003e regr.predict([[1, 1]])\narray([ 0.4])\n\u003e\u003e\u003e regr.partial_fit(X[1:], y[1:])\nOnlineSVR()\n\u003e\u003e\u003e regr.predict([[1, 1]])\narray([ 1.5])\n```\n\n## License\n\nPyOnlineSVR is free software under the terms of the GNU General Public License, as found in the [LICENSE](./LICENSE) file.\n\n## References\n\n\u003ca name=\"PAR2007\"\u003e[PAR2007]\u003c/a\u003e: Parrelly, Francesco (2007). \"Online Support Vector Machines for Regression.\" Master thesis. University of Genoa, Italy. [PDF](http://onlinesvr.altervista.org/Research/Online%20Support%20Vector%20Regression%20(Parrella%20F.)%20[2007].pdf)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FSebastianSchmidl%2Fpyonlinesvr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FSebastianSchmidl%2Fpyonlinesvr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FSebastianSchmidl%2Fpyonlinesvr/lists"}