What is the translation of " MULTICLASS " in Chinese?

• 多类
• 多类别

Examples of using Multiclass in English and their translations into Chinese

Multiclass logistic regression with gluon.
多类逻辑回归-使用Gluon.

And if it is multiclass.
如果是一个多类分类(Multi-classclassification).

Examples of multiclass classification problems:.
多类分类问题举例：.

And some work with binary and multilabel(but not multiclass) problems:.
有些工作与binary和multilabel（但不是多类）的问题:.

Then the multiclass MCC is defined as:.
然后multiclassMCC定义为:.

One, one trains K(K- 1)/ 2 binary classifiers for a K-way multiclass problem;
One（OvO）化简中，对于一个K类多元问题，训练K(K-1)/2个二元分类器；.

But we also have a multiclass classification problem.
但我们也有一个多类分类的问题。

Multiclass imbalance problems: analysis and potential solutions.
多类不平衡问题：分析和可能的解决办法。

The extension to networks with multiclass softmax outputs is straightforward.
将网络扩展到多类softmax输出是很直接的。

However, the CD algorithm implemented in liblinear cannot learn a true multinomial(multiclass) model;
然而，用liblinear库中实现的CD算法不能学习真正的多项式(多类)模型；.

User KNN to solve several binary and multiclass classification problems.
采用KNN解决一些二元和多类(multiclass)分类问题.

Finally, for multiclass problems, a softmax activation function of the form(4.62) is used.
最后，对于多分类问题，我们使用了式（4.62）给出的softmax激活函数。

Problems where more than two categories(classes) are available are called"multiclass classification" problems.
有两种以上的种类（类别）的问题被称作“多类别分类”问题。

A typical example of a multiclass classification task is handwritten character recognition.
多元分类任务的典型例子是识别手写字符。

Amazon ML supports three types of ML models: binary classification, multiclass classification, and regression.
AmazonMachineLearning支持三种类型的ML模型：二进制分类、多类别分类和回归。

Additional topics include multiclass classification, semi-supervised classification, active learning, and transfer learning.
附加的主题包括多类分类、半监督分类、主动学习和迁移学习。

However, the CD algorithm implemented in liblinear cannot learn a true multinomial(multiclass) model;
然而，在liblinear中实现的CD算法不能学习一个真正的multinomial(multiclass)多项（多类）模型;

Practical details of IRLS for the multiclass case can be found in Bishop and Nabney(2008).
多类别情况下的IRLS的实践细节可以参考BishopandNabney(2008)。

When using multiclass classifiers, the learning and prediction task that is performed is dependent on the format of the target data fit upon:.
当使用多类分类器时，执行的学习和预测任务取决于参与训练的目标数据的格式:.

For simplicity, the problem has been converted to a multiclass problem with classes as Young, Middle and Old.
为了简单起见，这个问题已被转换为类，如青年、中年和老年等多个类问题。

Multiclass classification refers to predicting multiple categories for example, when classifying an image as a picture of a specific breed of dog.
多类分类指的是预测多个类别（例如，当将图像划分为特定品种狗的图片）。

This section discusses strategies for reducing the problem of multiclass classification to multiple binary classification problems.
这部分讨论将多元分类问题化简为多个二元分类问题的策略。

In binary and multiclass classification, the Jaccard similarity coefficient score is equal to the classification accuracy.
在binaryandmulticlassclassification（二分和多类分类）中，Jaccardsimilaritycoefficientscore等于classificationaccuracy（分类精度）。

Note that you could also use Logistic Regression for multiclass classification, which will be discussed in the next section.
注意，你也可以将Logistic回归用于多类别分类，下一节中将会讨论。

Amazon Machine Learning supports three types of ML models: binary classification, multiclass classification, and regression.
AmazonMachineLearning支持三种ML模型：二进制分类、多类别分类和回归。

It includes algorithms for binary classification, multiclass classification, regression, structured prediction, deep learning, clustering, unsupervised learning, semi-supervised/metric learning, reinforcement learning and feature selection.
它包括诸多算法，可用于二进制分类、多类分类、回归、结构预测、深度学习、聚类、非监督学习、半监督/度量学习、强化学习和特征选择。

Amazon Machine Learning supports three distinct types of predictions: binary classification, multiclass classification, and regression.
AmazonMachineLearning支持三种类型的ML模型：二进制分类、多类别分类和回归。

Most often used for solving tasks of classification(binary), but multiclass classification(the so-called one-vs-all method) is also allowed.
大多数情况下被用来解决分类问题（二元分类），但多类的分类（所谓的一对多方法）也适用。

DecisionTreeClassifier is capable of both binary(where the labels are[-1, 1]) classification and multiclass(where the labels are[0,…, K-1]) classification.
DecisionTreeClassifier能够二进制（其中标签是[-1,1]）分类和多类（其中标签是[0，…，K-1]）分类。