minimum classification error criterion

基本解釋

In addition, the Nonlinear ADF is further optimized using Minimum Classification Error criterion.
同時，基於最小分類錯誤準(zhǔn)則對該函數(shù)進(jìn)行了優(yōu)化。
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This paper presents an efficient training algorithm for probabilistic neural networks using the minimum classification error criterion.
提出了一種基於最小分類錯誤準(zhǔn)則的概率神經(jīng)網(wǎng)絡(luò)的訓(xùn)練算法。
Minimum Classification Error(MCE) criterion based sub-words weighting parameters estimation algorithm is proposed in which the sub-word weighting parameters are derived by the MCE training.
本文提出了一種基於最小分類錯誤準(zhǔn)則（MCE）的子詞權(quán)重蓡數(shù)估計算法，通過MCE訓(xùn)練得到子詞的權(quán)重系數(shù)。