标记的数据 英语是什么意思 - 英语翻译

• labeled data
• labelled data
• flagged data
• in unlabeled data

在 中文 中使用 标记的数据 的示例及其翻译为 英语

标记的数据可用于诊断癌症。
Labelled data can be used in diagnosing cancer.

这将预先使用标记的数据，并且属于监督学习。
This uses labelled data in advance and falls under supervised learning.

但是需要大量有标记的数据。
But there's a huge need for labeled data.

例如，可以在整个组织中的文件服务器标记的数据。
For example, you could tag data in file servers across the organization.

标记的数据集是教师，它将训练您理解数据中的模式。
The labeled data set is the teacher that will train you to understand patterns in the data..

受访者被要求审查、修订和核实任何标记的数据，以便提交他们的调查。
Respondents were required to review, revise and verify any flagged data in order to submit their surveys.

如果没有标记的数据，它就无法识别自己的改进，因此它就不知道如何坚持每一个改进。
Without labeled data, it couldn't recognize its own improvements so it wouldn't know to stick with each improvement along the way.

无监督学习策略一般用在没有标记的数据中以发现隐藏结构（例如隐藏的马尔科夫链）。
Unsupervised learning strategies are typically used to discover hidden structures(such as hidden Markov chains) in unlabeled data.

预期输出称为标签，而输入数据就是“打了标记的数据”。
The expected output is called a label, and the data is‘labeled data'.

再者，非监督式学习试图在无标记的数据中找出隐藏的结构，这主要应用于集群、各种统计分布。
Furthermore, unsupervised learning tries to find a hidden structure in unlabeled data, and it's mostly used for clustering and various statistical distributions.

这是一个很重要的优点，因为未标记的数据比有标记的数据更多。
This is an important benefit because unlabeled data are more abundant than labeled data.

此外，若可以使用英语标记的数据，则这些方法可实现几乎免费的零样本转移。
Furthermore, if labelled data in English is available, these methods enable essentially free zero-shot transfer.

分类：样本属于两个或更多类，我们想从已经标记的数据中学习如何预测未标记数据的类别。
Classification: Samples belong to two or more classes and we want to learn from already labeled data how to predict the class of unlabeled data..

在这种情况下，我们可以使用人工标记的数据，因为相对较少的一部分查询占了很大一部分流量。
(You can feasibly use human­labelled data in this case because a relatively small fraction of the queries account for a large fraction of the traffic.).

但魔法背后往往意味着单调乏味的过程--精心标记的数据是许多深度学习项目的关键。
But behind that magic there's often drudgery- painstakingly labeled data is key to many deep learning projects.

在监督学习中，用户训练程序以基于已知和标记的数据集生成答案。
In supervised learning, the user trains the program to generate an answer based on a known and labeled data set.

标记的数据集是教师，它将训练您理解数据中的模式。
The label data set is a teacher that will train you to understand the patterns in the data..

在监督学习中，机器在有标记数据的帮助下进行训练，即，即带有正确答案标记的数据。
In Supervised learning, the machine is trained with the help of labelled data ie, data which is tagged with the right answers.

在监督学习中，机器在有标记数据的帮助下进行训练，即，即带有正确答案标记的数据。
In Supervised learning, the machine is trained with the help of labeled data, i.e., data that is tagged with the right answers.

分类(Classification):样本属于两个或多个类，我们希望从已经标记的数据中学习如何预测未标记的数据所属的类。
Classification: Samples belong to two or more classes and we want to learn from already labeled data how to predict the class of unlabeled data..

监督的方法依靠标记的数据。
Supervised methods rely on labelled data.

带日期/时间标记的数据存储20点.
Data storage with date/time stamp 20 points.

这种改进只发生在标记的数据上。
The advancements only happen with labeled data.

首先，它需要大量被标记的数据才能生效。
First, it requires a vast quantity of labeled data to be effective.

带日期/时间标记的数据存储20个点99个点.
Data storage with date/time stamp 20 points.

目前科学家通过大量人为做过标记的数据对AI进行训练；.
At present, scientists are training AI through a large amount of artificially labeled data;

为了训练神经网络做出决策，许多语言问题都需要手工标记的数据。
In order to train a neural network to make decisions, many language problems require data that's been meticulously labeled by hand.

主动学习是一种机器学习技术，可识别需要由人类标记的数据和可由机器标记的数据。
Active learning is a machine learning technique that identifies data that needs to be labeled by humans and data that can be labeled by machine.