片语

data dimensionality reduction数据降维

nonlinear dimensionality reductionHigh-dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret. One approach to simplification is to assume that the data of interest lie on an embedded non-linear manifold within the higher-dimensional space.

generalized multifactor dimensionality reduction使用广义多因子降维法

singular dimensionality reduction method单级降维技术

variable dimensionality reduction降维变量

image dimensionality reduction图像降维

Stepwise Dimensionality Reduction非参数信息边际距离最大化準则

dimensionality reduction property降维特征

英汉例句

• Locality Preserving Projections algorithm (LPP) is a new dimensionality reduction technique. But it is an unsupervised learning algorithm. It could not process classification effectively.

  局部保持投影(LPP)是一种新的数据降维技术，但其本身是一种非监督学习算法，对于分类问题效果不是太好。

• Part 2 is in the Projection Pursuit ideology high-dimensional data principal component analysis dimensionality reduction theoretical analysis and practical application;

  第2部分进行的是在投影寻蹤思想下对高维数据主成分分析降维的理论分析和实践应用；

• The original nonlinear dimensionality reduction algorithms are non-supervised, which can't directly be applied in pattern recognition.

  原始的非线性维数约减算法是无监督的，不能直接用于模式识别。

• Multidimensional scaling is a powerful tool for dimensionality reduction in the field of pattern recognition and data mining.

  多维尺度分析是模式识别与数据挖掘领域一个有力的降维工具。

• Most of the real-world data, such as images and videos, are always represented by tensor and high-dimensionality form, which make tensor data dimensionality reduction the hot issue in recent research.

  实际应用中的许多数据，如图像，视频，通常具有张量性和高维性特征，张量数据的维数约简便成为近期的研究热点。

• A new dimensionality reduction method for calculating the radiant heat transfer with two dimensional characteristics was introduced in this paper.

  针对具有二维特征的辐射传热问题，介绍了一种降维方法。

• A novel method for dimensionality reduction of kernel matrix is presented.

  提出了基于聚类的核矩阵维度缩减技术。

• The model selection principle of determining effective number of dimensionality reduction for different clusters is proposed.

  并提出了针对不同类簇判断有效降维维数的模型选择準则。

• Effective dimensionality reduction could make the learning task more efficient and more accurate in text classification.

  在文本分类中，有效的维数约简可以提高学习任务的效率和分类性能。

• Due to the supervised view of point, most of the present tensor dimensionality reduction methods cannot take full advantage of the unlabeled data.

  现有的张量维数约简方法大都是监督的，它们不能有效利用未标签样本数据的信息。

• In this paper we present an improved dimensionality reduction method based on support vector machines.

  提出了一种基于支持向量机的改进的降维方法。

• An uncorrelated kernel extension of graph embedding which provides a unified method for computing all kinds of uncorrelated kernel dimensionality reduction algorithms is proposed.

  提出统计不相关的核化图嵌入算法，为求解各种统计不相关的核化降维算法提供了一种统一方法。

• The Locaally 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。