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Software for Machine Learning

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Abstract

There are many sources for machine learning software. Machine learning encompasses machine learning software to help the user learn from data and software that helps machines learn and adapt to their environment. This book gives you a sampling of software that you can use immediately. However, the software is not designed for industrial applications. This chapter describes software that is available for the MATLAB environment. Both professional and open-source MATLAB software is discussed. The book may not cover every available package, as new packages are continually becoming available while older packages may become obsolete.

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References

  1. Behcet Acikmese and Scott R. Ploen. Convex programming approach to powered descent guidance for Mars landing. Journal of Guidance, Control, and Dynamics, 30(5):1353–1366, 2007.

    Article  Google Scholar 

  2. S. Boyd. CVX: MATLAB software for disciplined convex programming. http://cvxr.com/cvx/ , 2015.

  3. Chih-Chung Chang and Chih-Jen Lin. LIBSVM – A library for support vector machines. https://www.csie.ntu.edu.tw/~cjlin/libsvm/ , 2015.

  4. Philip Gill, Walter Murray, and Michael Saunders. SNOPT 6.0 description. http://www.sbsi-sol-optimize.com/asp/sol_products_snopt_desc.htm , 2013.

  5. Jos F. Sturm. Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones. http://sedumi.ie.lehigh.edu/wp-content/sedumi-downloads/usrguide.ps , 1998.

  6. R. J. Vanderbvei. LOQO user’s manual version 4.05. http://www.princeton.edu/~rvdb/tex/loqo/loqo405.pdf , September 2013.

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© 2017 Michael Paluszek, Stephanie Thomas

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Paluszek, M., Thomas, S. (2017). Software for Machine Learning. In: MATLAB Machine Learning. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-2250-8_3

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