What is the translation of " EACH DATA POINT " in Chinese?

• 每个数据点

Examples of using Each data point in English and their translations into Chinese

Put each data point in its own cluster.
将每个数据点放入其自己的群集中。

Also, we can see that it is based on each data point.
并且，我们能看到它基于每个数据点。

Associate each data point to the closest medoid.
将每个数据点分配给最接近的随机创建的中心。

Also, we can see that it is based on each data point.
同样，我们可以看到它基于每个数据点。

Then each data point is assigned to the closest centroid.
将每个数据点分配给最接近的随机创建的中心。

I would like to display each data point's series name.
现在，我们想对每个数据点进行分类。

Each data point is assigned to the closest cluster center.
将每个数据点分配给最接近的随机创建的中心。

Also, we can see that it is based on each data point.
此外，我们可以看到它基于每个数据点。

Randomly assign each data point to any of the 3 clusters.
将每个数据点随机分配给3个集群中的任何一个。

The spline must be continuous at each data point, that is.
样条在每个数据点都必须连续，即.

Assigns each data point to the closest of the randomly created centers.
将每个数据点分配给最接近的随机创建的中心。

ItemColorSet- The color of each data point in a chart.
ItemColorSet-图表中每个数据点的颜色。

Each data point forms a cluster with the closest centroids i.e. k clusters.
每个数据点形成具有最接近质心的簇，即K簇。

Use the standard deviation of the repeated measurements for each data point to make error bars.
使用对每个数据点的重复测量的标准偏差，使误差线。

Each data point forms a cluster with the closest centroids, i.e., K clusters.
每个数据点形成具有最接近质心的群集，即k个群集。

The view updates to show a line connecting each data point, and the Marks card updates with a Path button.
视图会进行更新以显示连接每个数据点的线，“标记”卡使用“路径”按钮进行更新。

Now each data point forms a cluster with the closest centroids, i.e., k clusters.
现在每个数据点形成一个具有最接近质心的簇，即k簇.

Also, the measurement itself takes a very long time in order to eliminate noise- each data point took four hours to obtain.”.
此外，测量本身要花费很长时间才能消除噪声，测量每个数据点都需要花费四个小时。

Each data point ran for one hour, with the database recreated before each run.
每个数据点运行一个小时，每次运行之前重新创建数据库。

As with the classification example, we have two-dimensional data: that is, there are two features describing each data point.
与分类示例一样，我们拥有二维数据：即，两个特征描述每个数据点。

Documentation for each data point so you can address site accessibility issues right away.
文档为每个数据点,所以你可以马上解决网站的可访问性问题。

Given these Gaussian distributions for each cluster, compute the probability that each data point belongs to a particular cluster.
给定每个群集的这些高斯分布，计算每个数据点属于特定群集的概率。

So, each data point produces values for every internal and output node in the neural network.
因此，每个数据点为神经网络中的每个内部和输出节点生成值。

It gives you information on how similar each data point is within your sample, which helps you determine if the data is significant.
它向你提供了样本中各数据点的相似性信息，有助于确定数据是否显著。

Each data point corresponds to a sentence and is coloured accordingly to the deep learning systems prediction and the true target.
其中每个数据点对应于一个句子，不同的颜色分别对应于该深度学习系统的预测和真实目标。

In supervised learning, each data point is labeled or associated with a category or value of interest.
监督学习：每个数据点被标记或者与一个类别或者感兴趣值相关联。

As an example, each data point could represent the amount of time in seconds that it requires a student to answer a particular exam question.
例如，每个数据点可以代表一个学生回答特定考试问题的时间长度（以秒为单位）。

You can start with a belief, but each data point will either strengthen or weaken that belief and you update your hypothesis all the time.
你可以从一个信念开始，但是每个数据点会加强或削弱这个信念，所以会一直更新假设。

You can start with a belief, but each data point will either strengthen or weaken that belief and you update your hypothesis all the time.
你可以从一个信念开始，但每个数据点要么加强要么削弱这个信念，你会一直更新你的假设。