Sentence examples for fixed misclassification from inspiring English sources

Exact(1)

Protocol II uses the LibSVM implementation of Support Vector Machines (SVMs) to build molecular signatures with a fixed misclassification penalty parameter C = 100, and a linear kernel [48].

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Though we carefully defined sepsis, shock and physiological criteria on the basis of objective measures within a fixed time period, misclassification of shock due to etiologies other than sepsis is a potential limitation of our study.

Measurement bias may also arise due to misclassification of fixed and variable costs.

The use of a fixed cutpoint also causes misclassification of airflow obstruction in younger adults (i.e., aged < 45 years), as has recently been shown by Cerveri and colleagues [ 18].

We examined only the radial function kernel for SVM with two a priori set kernel parameters γ = 0.5 and 2.0, and the parameter C (cost of misclassification) was also fixed at 10. Fixing these parameters may have resulted in "less than optimally trained" models that could lead to added variability in the performance of the classifiers.

The linear kernel has just one parameter (C) that controls the trade-off between having zero training errors and allowing misclassifications; this parameter was fixed at C = 1 for all cases (default value) in accordance with previous neuroimaging studies (e.g. [Mourao-Miranda et al., 2007]).

Table 1 shows the points that the total misclassification error of adopting the fixed combination (10, 30) is worse (higher error value) than utilizing the best combination of M and R for each noise type and SNR level shown in the subfigures.

However, this figure does not add substantial information to our results, since NRI (as well as IDI) refers to the misclassification occurring all along the risk scale, instead of capturing the misclassification which takes place around the fixed threshold.

A parameter C, which controls the tradeoff between having zero training errors and allowing misclassifications in the linear model, was fixed at C = 1 for all cases (default value).

We consider the time-varying exposure a major strength of our study, as the alternative, fixed exposure, would have led to extensive and unmeasurable misclassification yielding unreliable results.

The use of a fixed threshold to define airways obstruction is associated with some extent of misclassification.

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