What is the translation of " TRAINING EXAMPLES " in Chinese?

• 训练样例
• 训练实例
• 训练示例
• 训练样本
• 的训练例子

Examples of using Training examples in English and their translations into Chinese

Some specific training examples:.
具体训练举例：.

All the training examples will be merged in a single matrix X:.
所有的训练实例将合并在一个矩阵X中：.

Denote the number of training examples.
是训练实例的数量。

The training examples are vectors in a multidimensional feature space, each with a class label.
训练样本是多维特征空间向量，其中每个训练样本带有一个类别标签。

Denote the number of training examples.
是训练示例的数量。

Users can take advantage of these feature libraries and achieve great accuracy by learning from just a few hundred training examples.
最后，用户可以利用这些特征库，并通过几百个训练实例来获取更准确的信息。

Do you have enough training examples?
你有足够的训练实例吗？?

The typical use case is to discover the hidden structure and relations between the training examples.
典型的用例就是发现训练样例之间隐藏的结构或者关系。

N$ is the number of training examples.
这个$N$就是训练样本的数量。

For example, standard decision tree learners cannot learn trees with more leaves than there are training examples.
例如，标准的决策树学习器不能比具有训练样例的决策树学习更多。

Getting more training examples: Fixes high variance.
收集更多的训练样本--可解决highvariance问题.

Now we can calculate Z for all the training examples using:.
现在我们可以使用所有的训练例子计算Z：.

But it requires far fewer training examples, suggesting that it better replicates what the brain does.
但它需要较少的训练例子，这表明它更好地复制了人脑的运作。

The training data consist of a set of training examples.
训练数据由一组训练实例组成。

The model described in the paper has training examples that have a sentence(or caption) associated with each image.
本文中描述的模型有训练样例，每个图像都有一个句子（或标题）来描述。

The number below each task denotes the number of training examples.
每个任务下方的数字表示训练样例的数量。

If we have not yet observed any training examples, this distribution revolves around \mu=0, according to our original assumption.
如果还没观察到任何训练样本，该分布会如我们刚开始所假设的，围绕μ=0展开。

The training data herein consists of a set of training examples.
训练数据由一组训练实例组成。

This means that given a number of training examples, the system needs to be able to generalize to examples it has never seen before.
这意味着，系统需要通过给定的训练示例，在它此前并未见过的示例上进行泛化。

Thus, we have 3 input nodes to the network and 4 training examples.
因此，我们的神经网络有3个输入节点和4个训练实例。

To generate training examples, we started by gathering a large collection of 100,000 high-quality videos of lectures and talks from YouTube.
为了生成训练样本，我们首先从YouTube上收集10万个高质量讲座和演讲视频。

Thus, we have 3 input nodes to the network and 4 training examples.
这样，我们的神经网络便有3个输入节点，4个训练实例。

We feed in pairs of(book title, link) training examples with a mix of positive- true- and negative- false- pairs.
输入成对的训练示例，格式为（booktitle，link），其中的匹配有positive-true以及negative-false两种形式。

Expected generalization error can never increase as the number of training examples.
泛化误差的期望从不会因为训练样本数目的增加而增加。

The framework gives the robot a limited number of training examples and uses them to generalize to new objects.
通过他们的框架，机器人被给予有限数量的训练样例，并使用它们来推广到新对象。

Much of machine learning involves acquiring general concepts from specific training examples.
简介机器学习问题，一般都涉及从特殊训练样例中得到一般的概念。

Also, deep learning is poor at handling data that deviates from its training examples, also known as"edge cases.".
而且，深度学习在处理偏离其训练示例(也称为“边缘案例”)的数据方面很差。

Perhaps it becomes intuitive why we could have"loaded in" an arbitrary number of training examples.
也许这也能直观地解释：为什么我们可以“载入”任意数目的训练实例。

Luckily, the training data also includes background noise which we mix with our training examples at various volumes.
幸运的是，训练数据还包括背景噪声，我们将这些噪音与各种训练样例混合在一起。

One of Machine Learning's most successful paradigm is supervised learning which lets you build a generalization model by learning from a lot of training examples.
机器学习最成功的范例之一是监督学习（supervisedlearning），它允许您通过从大量训练实例中学习来构建泛化模型。