Sentence examples for accuracy of this classifier from inspiring English sources
The overall accuracy of this classifier is 92.7%.
Similar to user Study‐I, we used the Bayesian classifier based scheme and assessed the classification accuracy of this classifier to identify legitimate users.
The predictive accuracy of this classifier is determined using the test (set aside) examples with the same set of features.
The accuracy of this classifier in correctly diagnosing ASD cases from the second half of the dataset was 91%.
To calculate its accuracy on dataset D, we trained this classifier on dataset B and tested it on dataset D. The accuracy of this classifier on datasets E1 and E2 had already been reported by Borup et al. and we used those values for comparison.
The classification accuracy of the classifier in this independent dataset was 82.3% (825/1002), still significantly above the 50% we would have expected by chance.
The accuracy of this evolutionary classifier has been compared with other classifiers such as SVM [25], NN-BP [26], and KNN [3].
The accuracy of this univariate classifier peaked at 47.4 ± 1.3% in cross-validation (red trace).
The accuracy of this trivial classifier on the cross-validated corpus would be 73.7%.
This is because the accuracy of the classifier improves as the size of the training set increases and approaches the maximum accuracy possible for the problem at hand.
This was repeated until all pairs had been left out once and the accuracy of the classifier was determined by the correctly classified samples.
