What is the translation of " 维数 " in English?

• dimensionality
• dimensions
• dimension
• an array

Examples of using 维数 in Chinese and their translations into English

的维数诅咒.
Curse of Dimensionality.

一个平面有两个维数：长度和宽度，没有深度。
A plane has two dimensions- length and width, no depth.

为什么？电视是真实的，它是即时的，它具有维数。
The televisor is real, it is immediate, it has dimension.

降低数据维数将花费更少的时间来训练模型。
Reducing the dimension of data will take less time to train a model.

为什么宇宙表现为一个时间维数和三个空间维数?
Why does the universe appear to have one time and three space dimensions?

样本数(即n_samples)和维数(即n_features).
Number of samples(i.e. n_samples) and dimensionality(i.e. n_features).

分形基本上是系统维数的度量;
Fractals are basically a measurement of the dimensionality of a system;

与聚类方法一样，维数减少也是为了寻求数据的固有结构。
Like clustering methods, dimensionality reduction seeks an inherent structure in the data.

由于存在三个自由度，因此SO(3)的维数是3。
There are three degrees of freedom, so that the dimension of SO(3) is three.

Reshape(A,dims…)一个包含跟A相同数据但维数不同的数组.
Reshape(A, dims…) an array containing the same data as A, but with different dimensions.

图片的尺寸实际上就是这个二维数组的尺寸。
The dimensions of the picture is actually the dimensions of this two dimensional array.

池化还会降低输出维数，但（希望）可以保留最显着的信息。
Pooling also reduces the output dimensionality but(hopefully) keeps the most salient information.

真或假没有必要有一个用于应用维数降低算法的目标变量。
True or False It is not necessary to have a target variable for applying dimensionality reduction algorithms.

其维数为64，而嵌入和编码器的输入/输出向量的维度为512。
Their dimensionality is 64, while the embedding and encoder input/output vectors have dimensionality of 512.

通常情况下这个代数非常巨大（维数不可数），但常常可以替换成一个小得多的代数。
This algebra is usually very large(uncountable dimension) but can be replaced by a much smaller algebra.

在Fourier[list]中给出的list可以嵌入表达一个任何维数的数据数组。
The list given in Fourier[list] can be nested to represent an array of data in any number of dimensions.

嵌入式投影机具有降低数据集维数的三种方法：两个线性和一个非线性。
The Embedding Projector has three methods of reducing the dimensionality of a data set: two linear and one nonlinear.

只考虑前N（例如，N=70）个特征向量，特征空间的维数大大减少了。
By only considering the first N(e.g. N=70) eigenvectors, the dimensionality of the feature space is greatly reduced.

维数约简对于应对大数据（像每秒钟通过你的知觉而进入的数据）来说很关键。
Dimensionality reduction is essential for coping with big data- like the data coming in through your senses every second.

在InverseFourier[list]中给出的list可以嵌套来表示任何维数的数据数组。
The list given in InverseFourier[list] can be nested to represent an array of data in any number of dimensions.

这个定义说明了哪些概念是维数（确认和描述），哪些概念是属性（只是描述）。
It tells us which concepts are the dimensions(identification and description) and which are attributes(just description).

维数减少将估计p+1个系数的问题简化为M+1个系数的简单问题，其中M.
Dimension reduction reduces the problem of estimating p+ 1 coefficients to the simple problem of M+ 1 coefficients, where M< p.

空间，一个巨大的空盒子，有三个维数：长度，宽度和深度，在三个方向同时伸向无穷远。
Space, a huge empty box, has three dimensions, length, width, and depth, extending to infinity in all three directions.

由于数据将被映射到最大特征向量来减少维数，所以需要获得特征分解。
Since the data will be projected onto the largest eigenvectors to reduce the dimensionality, the eigendecomposition needs to be obtained.

有效的特征选择可以降低维数，提高预测精度，提高结果的可理解性。
Effective feature selection could help reduce dimensionality, improve prediction accuracy and increase result comprehensibility.

分离新的不同维数碳同素异形体是过去二三十年研究的焦点，科学。
Synthesizing and separating new carbon allotropes of different dimensions has been the focus of research in the past twenty or thirty years.

Nanorobots是被设计的精华nanoelectromechanical系统执行一项特定任务与精确度在nanoscale维数。
Nanorobots are quintessential nanoelectromechanical systems designed to perform a specific task with precision at nanoscale dimensions.

控制随机投影矩阵的维数和分布，以便保留数据集的任意两个样本之间的成对距离。
The dimensions and distribution of random projection matrices are controlled so as to approximately preserve the pairwise distances between any two samples of the dataset.

最终，曼德博在1975年提出了“碎形”一词，来标记一个豪斯多夫-贝西科维奇维数大于拓扑维数的物件。
Finally, in 1975 Mandelbrot coined the word"fractal" to denote an object whose Hausdorff-Besicovitch dimension is greater than its topological dimension.

EmbeddingProjector提供了三种常用的数据维数降低方法，允许更容易地显示复杂数据：PCA、t-SNE和定制线性投影。
The Embedding Projector offers three commonly used methods of data dimensionality reduction, which allow easier visualization of complex data: PCA, t-SNE and custom linear projections.