Training and testing the data

조회 수: 2 (최근 30일)
nkumar
nkumar 2013년 1월 7일
댓글: Son Dong 2020년 10월 13일
I got a code from net for SVM classifier
clc
clear all
load fisheriris %# load iris dataset
groups = ismember(species,'setosa'); %# create a two-class problem
%# number of cross-validation folds:
%# If you have 50 samples, divide them into 10 groups of 5 samples each,
%# then train with 9 groups (45 samples) and test with 1 group (5 samples).
%# This is repeated ten times, with each group used exactly once as a test set.
%# Finally the 10 results from the folds are averaged to produce a single
%# performance estimation.
k=10;
cvFolds = crossvalind('Kfold', groups, k); %# get indices of 10-fold CV
cp = classperf(groups); %# init performance tracker
for i = 1:k %# for each fold
testIdx = (cvFolds == i); %# get indices of test instances
trainIdx = ~testIdx; %# get indices training instances
%# train an SVM model over training instances
svmModel = svmtrain(meas(trainIdx,:), groups(trainIdx), ...
'Autoscale',true, 'Showplot',false, 'Method','QP', ...
'BoxConstraint',2e-1, 'Kernel_Function','rbf', 'RBF_Sigma',1);
%# test using test instances
pred = svmclassify(svmModel, meas(testIdx,:), 'Showplot',false);
%# evaluate and update performance object
cp = classperf(cp, pred, testIdx);
end
%# get accuracy
cp.CorrectRate
%# get confusion matrix
%# columns:actual, rows:predicted, last-row: unclassified instances
cp.CountingMatrix
In comment
%If you have 50 samples, divide them into 10 groups of 5 samples each,
%# then train with 9 groups (45 samples) and test with 1 group (5 samples).
I have 5x6 samples
have divided 5x4 to training and 5x2 for testing
now please tell how to process above mentioned step

답변 (2개)

liu xiaolong
liu xiaolong 2013년 3월 13일
Hello!Can you give me the code of the function svmtrain? Thank you very much.

noo no
noo no 2015년 10월 17일
i have code in matlab how trining and testing this code?
  댓글 수: 1
Son Dong
Son Dong 2020년 10월 13일
Can you give me please. Thank you so much.

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