Sentence examples for a classification error from inspiring English sources

Spinner and several of the other defense lawyers learned more about the C.I.A.'s role in Jamadi's death than they were supposed to know, owing to a classification error made by the agency.

Did a classification error doom a fish called a slapper skate to near extinction?

Since in such cases a classification error could frequently have serious consequences, the classifiers employed should ensure a very high reliability to avoid erroneous decisions.

Fig. 6 Estimation error rate under different reference NNs Fig. 7 a Classification error rate under a different number of target goods.

The errors can be produced in two ways: first, a classification error due to a bad labeled frame, and a segmentation error due to a temporal mismatch between the reference boundaries and the hypothesis boundaries.

In order to reduce the effect of noise on the hyperplane, the SVM model allows the existence of the deviation point when constructing the hyperplane, i.e. there is a classification error.

We identified 1089 peptides that were exclusively recognized in the TB+ group (Figure 3, left panel), 1001 in the TB− group (Figure 3, right panel) and 89 common peptides that were predictive of the groups by PAM analysis (see cluster image in Figure 4) with an classification error of approximately zero.

> The major cause for article misclassification is a direct result of a sentence classification error: the relevant deposition sentence was assigned a score below the threshold.

A low classification error rate in an MDR model indicates a high statistically significant risk of n-loci effects.

The analyses, carried out in the near and mid-infrared (NIR MIR) spectral field (1280 4480 nm), show that glass ceramic and glass fragments can be recognized by applying a wavelet transform, with a small classification error.

FMDR includes the following advantages: (1) FMDR can effectively reduce the computational time required by MDR for high-order interactions, (2) the best model has a low classification error rate and a high sensitivity for disease prediction, and (3) FMDR can easily be combined with existing MDR methods.