How to train SVM
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Hi, Is there anyone who will help me in SVM for classification in Matlab code. i have completed my work until feature extraction and after feature extraction, I have created mxn size of the matrix where n is the number of samples and mx1 is the array of each image/character.
Please guide that, how I have to arrange the training dataset that I can train SVM.
采纳的回答
Walter Roberson
2018-5-8
"Input Arguments:
Train: Matrix of training data, where each row corresponds to an observation or replicate, and each column corresponds to a feature or variable."
That is already the form that your indicate your data is in, so you do not need to do anything further to prepare it. Just call
svmtrain(YourMatrix, Vector_of_target_information)
5 个评论
Ameer Hamza
2018-5-8
neha gautam
2018-5-8
neha gautam
2018-5-8
Walter Roberson
2018-5-8
What is class(tar) and size(tar) ?
neha gautam
2018-5-8
更多回答（2 个）
Ameer Hamza
2018-5-8
The easiest way to get started and visualize is to use Classification Learner App. Start it using this command
classificationLearner
Then you can start a new session. Import your data. In the model type choose SVM. Several SVM models are available. Choose advanced and choose advanced training options. Then press train to start training. When Training is complete, it will visualize result using several graphs. You can also export the model to the workspace for further processing.
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