Support Vector Machines w/ JAVA & SMO (Sequential Minimal Optimization) |
prototypeprj.com = zaneacademy.com (version 2.0) |
00:07 demo a prebuilt version of the application 01:50 code the application 02:11 go over the various classes that make up the app. 03:08 go over the training data used in this app. 03:52 setup and use the commons math jar to do matrix operations 04:33 start the initial coding of the SupportVectorMachines class 05:20 quick introduction to Support Vector Machine (SVM) 06:46 quick introduction to Sequential Minimal Optimization (SMO) 07:50 resume coding the application SupportVectorMachines class 09:41 plug in equation for 'w' into equation of a linear svm and use resulting equation in code 10:40 EPSILON and slack penalty C 11:02 alpha and the violation of KKT conditions 11:54 selecting the index of the 2nd alpha to optimize 13:26 optimize an alpha pair and b 15:15 define and calculate w 15:37 classify method 16:12 display information tables code 16:54 handle command line entry code 17:12 JavaFX display code 18:14 explain + test run the application 19:27 change C and rerun app. to show overfitting ----------------------------------------------------------------------------------------------------------------------------- quickly download, import into Eclipse, and run zip file for 'Support Vector Machines w/ JAVA & SMO (Sequential Minimal Optimization)' ------------------------------------------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------------------- download source code @https://sites.fastspring.com/prototypeprj/instant/ai ----------------------------------------------------------------------------------------------------------- |
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Tuesday, July 14, 2020
Support Vector Machines (SVM) w/ JAVA & Sequential Minimal Optimization (SMO)
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