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%。
The experimental results show that the proposed method can fuse multiple classifiers with low classification error rate based on comprehensible fuzzy systems.
实验结果表明，该方法能够用可理解性好的模糊系统实现低错误率的多分类器融合。
Experimental results show that phonetic classification based on the triphone can greatly improve system performance. The proposed method reduces the error rate by 28% compared with a baseline system.
实验表明：基于语音学分类的三音子单元对识别性能有明显的改善，系统的首选误识率相对基线系统降低了28%。
Minimum classification error (MCE) rate method is the most straightforward criterion for HMM training. Inprinciple, it is much better than the maximum likelihood method.
最小错识率(MCE)HMM训练方法是最直接的判决训练方法之一，原理上比最大似然接方法优越得多。
Minimum classification error (MCE) rate method is the most straightforward criterion for HMM training. Inprinciple, it is much better than the maximum likelihood method.
最小错识率(MCE)HMM训练方法是最直接的判决训练方法之一，原理上比最大似然接方法优越得多。
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