如何分割秧雞分類器的比例在MATLAB

怎麼辦秧雞分類的分割比例在MATLAB 喜有下面的代碼，但我不能得到分流百分比則顯示錯誤如何分割秧雞分類器的比例在MATLAB

javaaddpath('weka.jar'); 
import weka.core.Instances.* 
import weka.classifiers.functions.supportVector.* 
%import weka.core.converters.ConverterUtils$DataSource.* 
filename = 'c.arff'; 
filename1 = 'ctest.arff'; 
cross='10'; 
reader = javaObject('java.io.FileReader', filename); 
data = javaObject('weka.core.Instances', reader); 
if (data.classIndex() == -1) % -1 means that it is undefined 
    data.setClassIndex(data.numAttributes() - 1); 
end 
c = weka.classifiers.functions.SMO();  
    c.setC(100); 
    k = weka.classifiers.functions.supportVector.Puk(); 
    k.setOmega(1.0); 
    k.setSigma(1.0); 
    c.setKernel(k); 
c.buildClassifier(data); %% "data" here is the training data 

% evaluate model (simple evaluation over training set) 
ev = weka.classifiers.Evaluation(data); % "data" here is the test data 
    v(1) = java.lang.String('-t'); 
    v(2) = java.lang.String(filename); 
    v(3) = java.lang.String('-T'); 
    v(4) = java.lang.String(filename1); 
    v(5) = java.lang.String('-split-percentage'); 
    v(6) = java.lang.String('80'); 
    v(7) = java.lang.String('-i'); 
    params = cat(1,v(1:end)); 
ev.evaluateModel(c, params)

來源

2013-08-23 user2490712

這裏我的問題的答案爲10倍交叉驗證MATLAB代碼是

javaaddpath('weka.jar'); 
import weka.core.Instances.* 
import weka.classifiers.* 
filename = 'c.arff'; 
reader = javaObject('java.io.FileReader', filename); 
data = javaObject('weka.core.Instances', reader); 
if (data.classIndex() == -1) % -1 means that it is undefined 
    data.setClassIndex(data.numAttributes() - 1); 
end 
c = weka.classifiers.trees.J48(); 
c.buildClassifier(data); 
ev = weka.classifiers.Evaluation(data); % "data" here is the test data 
    v(1) = java.lang.String('-t'); 
    v(2) = java.lang.String(filename); 
    v(3) = java.lang.String('-x'); 
    v(4) = java.lang.String('10'); 
    v(5) = java.lang.String('-i'); 
    params = cat(1,v(1:end)); 
ev.evaluateModel(c, params)

答案爲分類的比例拆分

javaaddpath('weka.jar'); 
import weka.core.Instances.* 
import weka.classifiers.* 
filename = 'c.arff'; 
reader = javaObject('java.io.FileReader', filename); 
data = javaObject('weka.core.Instances', reader); 
if (data.classIndex() == -1) % -1 means that it is undefined 
    data.setClassIndex(data.numAttributes() - 1); 
end 
c = weka.classifiers.trees.J48(); 
c.buildClassifier(data); 
ev = weka.classifiers.Evaluation(data); % "data" here is the test data 
    v(1) = java.lang.String('-t'); 
    v(2) = java.lang.String(filename); 
    v(3) = java.lang.String('-split-percentage'); 
    v(4) = java.lang.String('80'); 
    v(5) = java.lang.String('-i'); 
    params = cat(1,v(1:end)); 
ev.evaluateModel(c, params)

來源

2013-08-23 15:44:57 user2490712

如何分割秧雞分類器的比例在MATLAB

回答

相關問題