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How much classification bias is affordable depends on the joint interaction of spatial resolution and fragmentation.
In general, such error can be classified as selection bias, classification bias or confounding bias.
By reasoning in terms of landscape fragmentation and spatial resolution, the proposed framework decouples the resolution bias and the classifier bias from the overall classification bias.
In particular, by taking full advantage of xk's nearest neighbors, classifiers are able to reduce classification bias and variance when classifying xk.
Due to the dichotomization of urban versus non-urban for data analysis, there is the risk of classification bias.
To avoid classification bias, the patients received their medical diagnosis by a specialist in chronic TMD in order to be classified in the correct group.
We observed that read speech was better recognizable than spontaneous speech (see Fig. 17), which we believe is partially a result of classification bias, but also a result of the higher diversity of spontaneous speech class examples.
Classification bias is unlikely to have occurred since the whole processing was blinded to drug exposure.
This method is commonly used to reduce classification bias and estimate future model performance [40].
Moreover, this classification bias might not be related to time.
Second, a classification bias is possible due to the use of an imperfect gold standard.
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