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降维

网络Dimensionality Reduction; dimension reduction; Reducing dimensions

降维

网络释义

降维

Dimensionality Reduction

通过降维（Dimensionality Reduction）把事物更加一般化地表现出来。这种方法在计算量上要密集得多，不过随着计算机的发 …

dimension reduction

许多包结合了降维（dimension reduction）和分类。klaR包可以做变量选择，可处理多重共线性，还有可视化函数。

Reducing dimensions

问卷统计分析与SPSS应用 - MBA智库文档 ... Predicted value, 预测值 Reducing dimensions, 降维 Sequential method, 贯序法 ...

Data Reduction

spss新手入门 ... Classify 聚类和判别分析 Data Reduction 降维,简化数据过程 ……2-stage Least Squares 二阶最小平方回归分 …

例句：

By the singular value decomposition (SVD) of this sparse matrix , the high dimensions of image database feature matrix can be reduced.

对此矩阵进行奇异值分解，以实现高维图像特征库降维；

Meanwhile, combined with the sorts distributing, it once more reduced the feature dimension .

同时结合特征的类别分布进行了二次特征降维。

In spectral reflectance reproduction based color correction , the finite dimension model can be employed to condense spectral reflectance .

在基于光谱反射率还原的颜色校正方法中，有限维模型是光谱反射率降维的有效方法。

As a new learning framework , the diffusion method realizes dimensionality reduction in a diffusion processing .

作为一种新的流形学习框架，扩散映射通过在扩散过程中保持扩散距离进行降维。

The hidden manifold in the high dimensional space can be successfully embedded to a low dimensional space using KPCA.

核主元分析是一种非线性降维算法，能够把这种流形结构嵌入到低维空间。

The result of SVD is the input and the number of classification equals the number of output -layer nodes .

人脸降维后的结果作为 BP 网络的输入，网络输出节点数就是分类数。

The Locally Linear Embedding (LLE) algorithm is an effective technique for nonlinear dimensionality reduction of high-dimensional data.

局部线性嵌入（LLE ）算法是有效的非线性降维方法，时间复杂度低并具有强的流形表达能力。

As an extension of two-dimensional C-V model , Three-dimensional C-V model avoids dimensional reduction.

作为二维 C-V 模型的推广，它避免了原先需对三维体数据进行降维的缺点。

Subsequently , principal component analysis (PCA) is used for dimensionality reduction.

然后，采用主成分分析法进行特征降维；

Neighborhood selection is one of the most important link in low-dimensional representations of high-dimensional data sets.

对高维数据进行降维时，邻域选取是一个非常重要的环节。

The singular perturbation algorithm is proposed to reduce the system dimension .

采用奇异摄动算法使系统降维。

In this paper, the descending dimension algorithm for nonlinear programming problems with linear equality constraints are discussed.

本文研究含有线性等式约束的非线性规划问题的降维算法。

This paper describes methodologies of dimension reduction algorithm and index structure to solve dimension reduction problem .

阐述了用降维算法和构建索引结构来解决高维数据降维问题。

In order to obtain relatively stable result , this paper probes into a reducing dimension algorithm on ill_posed error equation .

探讨了基于拟合误差方程病态的降维处理算法，以期得到稳定的解。

As a result, dimension reduction is one of the key steps of hyperspectral image processing. There are two ways for dimension reduction.

高光谱图像降维有两种方法，一种方法是特征提取，另一种方法是波段选择。

The minimum number of causality judgement indicators of ADR was determined by dimension reduction method .

运用降维技术探讨 ADR 因果关系判断的最小因子数。

It also helps to judge if the optimal solution is global optimal solution according to its position in the design space .

根据优化轨迹从优化结果在降维空间中的位置能够判断优化结果是否具有全局最优解特性。

Then , through solving the slow time-scale problem by optimal control theory , the optimal reduced -order reference trajectory is obtained .

然后，应用最优控制理论得出慢时间尺度上的解，并将其作为降维后的最优参考轨迹；

Secondly, a new weighted principal component analysis (PCA) method was designed to lower dimension for sample matrixes.

接着设计出了一种加权 PCA 方法用于对样本矩阵进行降维；

The trick is to find an arrangement of springs that "flattens" the data set , or in other words , reduces its dimensionality .

而诀窍就是找到一个弹性阵列，能够将非单调的数据集 “变成单调数据集 ”，或者换言之，就是降维。

降维

降维

Dimensionality Reduction

dimension reduction

Reducing dimensions

Data Reduction

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