I am going to classify multispectral remote sensing image using SVM .
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I have written a code for classifying three crops using SVM training , The three crops are cotton ,wheat and gram. Now to get more accuracy I want to optimize the training data using genetic algorithm then I wish to train the optimized data using SVM train and then want the classification result . First want to compare the result with simple SVM algorithm , I am attaching the codes here please help me to correct that code so that i could get the better kappa coefficient .ore if u suggest some other parameters of comparison of two techniques . One more thing is please suggest me how to use kernels in SVMtrain instruction ..!
2 个评论
Hardik Nadiyana
2017-3-27
generating error on kappa time i am using matlab 14. please help me out!
Vijaya pardha saradhi Tummala
2018-5-9
find kappa function is not available can you please update!
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Shashank Prasanna
2014-4-11
0 个投票
The following section in the documentation shows how you can use cross validation to tune your svm parameters using optimization:
Go through the examples and how-to's in this link, that should answer most of your questions:
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