Statistical Machine Learning and Dissolved Gas Analysis Companion code for the paper: "Statistical Machine Learning and Dissolved Gas Analysis: A Review" P Mirowski, Y LeCun Power Delivery, IEEE Transactions on, 2012 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6301810 http://www.cs.nyu.edu/~mirowski/pub/PiotrMirowski_IEEEPowerDelivery_2012_Final.pdf An appendix to the paper submission "Statistical Machine Learning and Dissolved Gas Analysis: A Review" that describes the machine learning algorithms with further details, is available at: http://cs.nyu.edu/~mirowski/pub/dga/MLreview4DGOA_Appendix.pdf Requirements: The following libraries need to be installed (and the Matlab paths configured accordingly): LibSVM with Matlab interface, available at: http://www.csie.ntu.edu.tw/~cjlin/libsvm/ Low-Density Separation, available at: http://olivier.chapelle.cc/lds/ The Matlab Statistics Toolbox Installation: After download, unzip and configure the required paths. Tutorial: In directory Code_Duval, execute under Matlab the following file: Duval.m License: Please refer to the GNU General Public License, available at: http://www.gnu.org/ References for the data: M. Duval and A. dePablo, "Interpretation of gas-in-oil analysis using new IEC publication 60599 and IEC TC 10 databases", IEEE Electrical Insulation Magazine, vol. 17, pp. 3141, 2001.