The classification error rate for normal and early stage DR samples reached 21.35% using a linear classifier and the leave-one-out method.
使用线性分类器进行分类，并用“留一法”统计结果，正常人和早期DR病例的分类错误率为21.35%。
Then patterns are categorized by the designed fuzzy inference regulation. The design of this piecewise linear classifier enhances the ability of linear classification of the algorithm.
然后，通过设计的模糊推理规则进行模式的分类，这种分段线性分类器的设计提高了算法线性分类的能力。
At last, according to the line character we designed the classifier to obtain the object image including linear distress and nonlinear ones.
然后根据裂缝的线性特征，设计分类器，得到包含裂缝及非裂缝的线性目标图。
When a new data fed into the integrated model, a classifier will deliver the new data into different non-linear local ANN model.
当新的信息进入该模型时，首先用分类器判别其类别，以确定用混合模型中的何种局部模型加以模拟。
When a new data fed into the integrated model, a classifier will deliver the new data into different non-linear local ANN model.
当新的信息进入该模型时，首先用分类器判别其类别，以确定用混合模型中的何种局部模型加以模拟。
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