www.gusucode.com > stats 源码程序 matlab案例代码 > stats/SaveCompactSVMModelForCodeGenerationExample.m
%% Save SVM Model for Code Generation % To generate C code that classifies new observations based on a % trained SVM model, you must first save the trained model to disk. This % example shows how to perform this first step. %% % Load the |ionosphere| data set. load ionosphere %% % Train an SVM classification model using the entire data set. % Specify to standardize the data. Mdl = fitcsvm(X,Y,'Standardize',true); %% % |Mdl| is a |ClassificationSVM| model. %% % Save the SVM classification model to the file |'SVMIonosphere.mat'|. saveCompactModel(Mdl,'SVMIonosphere'); %% % |'SVMIonosphere.mat'| appears in your present working directory. % |saveCompactModel| reduces the memory footprint of the model by removing % properties that are not needed for prediction, for example, the training % data. Then, |saveCompactModel| saves a structure array that characterizes % |Mdl| in |'SVMIonosphere.mat'|. %% % In the function that you declare that classifies new data using the % trained SVM model, load the structure array in |'SVMIonosphere.mat'|.