In this study, SVM model was trained by data from 100
samples (50 conventional+50 hybrid) for the training set,
calibrated by comparing to the true type, and used to predict
20 other samples (10 conventional+10 hybrid) for the
testing set. This model was corresponded to the data from
electronic tongue, nose, and the combination of both,
which were reduced by PCA and LLE algorithms,
respectively
In this study, SVM model was trained by data from 100samples (50 conventional+50 hybrid) for the training set,calibrated by comparing to the true type, and used to predict20 other samples (10 conventional+10 hybrid) for thetesting set. This model was corresponded to the data fromelectronic tongue, nose, and the combination of both,which were reduced by PCA and LLE algorithms,respectively
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