One of the steps of data preprocessing is dimensionality reduction.
维数约简是数据预处理的步骤之一。
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。
Feature selection and feature extraction are common methods for dimensionality reduction.
特征选择和特征抽取是维数约简常用的两种方法。
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。
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。
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。
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准则。
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。
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。
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。
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。
Dimensionality reduction algorithms, as the key technologies of data preprocessing in intelligent recognition, have been used successfully recently.
近年来降维方法作为智能识别中关键的数据预处理技术得到了较为成功地运用。
Manifold learning attempts to obtain the intrinsic structure of non-linearly distributed data, which can be used in non-linear dimensionality reduction(NLDR).
流形学习旨在获得非线性分布数据的内在结构，可以用于非线性降维。
Objective To introduce the application of Multifactor Dimensionality Reduction (MDR) method for detecting gene-gene interactions in genetic case-control studies.
目的介绍在遗传流行病学病例对照研究中，应用多因子降维法（MDR）分析基因-基因交互作用。
The algorithm is impractical on large data sets, unless it USES dimensionality reduction, sampling, or partitioning - all of which reduce recommendation quality.
在大数据集的情况下，这样的算法不可行，除非使用维度降低、抽样或区隔——所有这些都降低了推荐的品质。
2014-2016, Image Hashing Theories and Methods Based on Data Dimensionality Reduction and Compressive Sensing, National Natural Science Foundation of China (NSFC), PI.
基于数据降维和压缩感知的图像哈希理论与方法，国家自然科学基金（青年科学基金项目）， 2014-2016，主持。
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踪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；
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。
Dimensionality reduction applied to the customer space effectively groups similar customers into clusters; as we now describe, such clustering can also degrade recommendation quality.
向顾客空间应用维度降低技术，能有效地把相似顾客组合为群组，正如我们现在所说的，这样的聚类也会降低推荐的品质。
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。
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。
Such technique pursues, through the study of the eigenvalues, the reduction of the dimensionality in the representation space.
这种方法是通过对特征值的研究，追求表征空间的维数压缩。
Such technique pursues, through the study of the eigenvalues, the reduction of the dimensionality in the representation space.
这种方法是通过对特征值的研究，追求表征空间的维数压缩。
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