是未分类错误的主要代码。
表示的是指示发生了未分类错误的事件代码。
Represents the event code indicating that an unclassified error occurred.
仔细研究此输出，您可以查找文档并分析它分类错误的原因。
Digging into this output, you can look up document and examine it for clues as to why it might have been incorrectly classified.
同时，基于最小分类错误准则对该函数进行了优化。
In addition, the Nonlinear ADF is further optimized using Minimum Classification Error criterion.
采用该方法对歌词内容分类错误的类别标记进行修正。
The combing method USES the lyrics right labels to correct the content of music wrong labels.
在很多应用中，组合使用多个分类器可以降低分类错误率。
In a wide range of applications, the combination of classifiers leads to substantial reduction of misclassification error.
提出了一种基于最小分类错误准则的概率神经网络的训练算法。
This paper presents an efficient training algorithm for probabilistic neural networks using the minimum classification error criterion.
提出了一种基于最小分类错误准则的概率神经网络的训练算法。
This paper presents a training algorithm for probabilistic neural networks using the MCE criterion.
特征提取的目的是获取特征数目少且分类错误概率小的特征向量。
The purpose of feature extraction is to obtain feature vectors of few number and low error probability.
实验结果表明，训练集比例至少为50%时才能使分类错误率达到相对平稳。
Results show that proportion of train-set needs to be at least 50% for a comparatively stable error-rate.
另外，许多分类错误是由SAR图像的像素点类别混淆和相干斑噪声干扰引起的。
Besides, many classification errors are caused by mixed pixels and speckle noise of the SAR image.
首先，提出了一种基于分类错误分布的混淆类识别技术，识别预定义类别中的混淆类集合。
In this paper, firstly a technique for confusion class recognition based on classification error distribution is proposed to recognize confusion class sets existing in the pre-defined taxonomy.
提出了一种基于最小分类错误(MCE)训练的采用多层感知器(MLP)结构的模式分类器设计方法。
An improved design method on pattern classifier based on multi-layer perceptrons (MLP) by means of minimum classification error (MCE) training was proposed.
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 classification error rate for normal and early stage DR samples reached 21.35% using a linear classifier and the leave-one-out method.
本文提出了一种基于最小分类错误准则(MCE)的子词权重参数估计算法，通过MCE训练得到子词的权重系数。
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.
传统的反向传播神经网络(BPNN)学习以分类错误最小为目标，通常假定在分类错误时所有样本的代价完全相同。
The learning of Backpropagation Neural Network (BPNN) aimed at lowering the classification error, usually assuming that all the samples had equal price when misclassifications were made.
它现在被列在分类广告上，没有打印错误或印刷错误。
It is now listed in the classifieds, with no typos or misprints.
似乎普查局只是将一大部分网上销售错误分类了。
It seems likely that Census simply misclassifies a large chunk of online sales.
我们经常认为绘画需要天赋，但这种想法源于我们的错误分类——绘画主要是一种艺术形式，而不是一种学习工具。
We often think of drawing as something that takes inborn talent, but this kind of thinking stems from our misclassification of drawing as, primarily, an art form rather than a tool for learning.
这些错误表明在我们的模型中出了问题，我们的模型正在错误地分类某些数据。
These errors indicate we have problems in our model, as the model is incorrectly classifying some of the data.
请注意这里提到的一个问题：在分类问题中，学习算法的目标是把给定输入中的错误最小化。
Notice something important here: in the classification problem, the goal of the learning algorithm is to minimize the error with respect to the given inputs.
在系统中创建额外的规则有助于更正错误分类的案例。
The creation of extra rules in the system helps to correct wrongly classified cases.
虽然可能会出现不正确的分类，但可接受的错误百分比由模型创建者决定。
While some incorrect classifications can be expected, it's up to the model creator to determine what is an acceptable percentage of errors.
在我们需要设计一个企业系统架构时，作为知识主要来源的涉众甚至是错误的分类。
Stakeholders are even the wrong category to be used as a primary source of knowledge when we need to architect an enterprise system.
我使用两个主要的度量值来分类AIX系统上的磁盘错误：影响和持续时间。
I use two main areas to categorize disk errors on AIX systems: impact and duration.
本文首先概述了磁盘错误及其分类。
It starts with an overview of disk errors and their categorization.
错误可以分类为以下几组。
category：抛出一个500错误，这是因为缺少分类id。
Category: throws a 500 error, due to the missing category id.
category：抛出一个500错误，这是因为缺少分类id。
Category: throws a 500 error, due to the missing category id.
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