• Feature reduction method involves feature selection and feature extraction.

    降维的主要方法是特征选择和特征提取。

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  • Feature reduction can generally fall into feature extraction or feature selection.

    特征约简可通过特征提取或特征选择实现。

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  • Therefore, it is necessary to perform feature reduction for every decision of the shot boundary.

    因此,有必要对每一个镜头检测决策进行特征约简。

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  • Therefore, it is necessary to perform feature reduction for the decision rules of shot boundary.

    因此,有必要对镜头边界检测的规则进行特征约简。

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  • A neural network numeral recognition method based on feature extraction and rough set feature reduction is proposed for numeral recognition of non-pointer instrument dial.

    针对无指针式仪表表盘的数字识别问题,提出了一种基于特征提取和粗糙集特征约简的神经网络数字识别方法。

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  • The method combined CHI value feature selection and rough set theory fully so as to avoid both feature reduction on a large scale decision table and the discretization of the decision table.

    该方法将CHI值特征选取和粗糙集理论充分结合,避免了用粗糙集对大规模决策表进行特征约简,同时避免了决策表的离散化。

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  • To overcome the shortage of information gain in text categorization, this paper proposes a method of feature reduction based on the relative document frequency balance information gain (RDFBIG).

    针对文本分类中信息增益降维方法的不足,提出了一种基于相对文档频的平衡信息增益(RDFBIG)降维方法。

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  • Therefore, they would be the worst hit and most irritated by a reduction of the feature set.

    因此,如果特性集缩减了,最容易恼怒和受到打击的就是这些客户。

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  • You can implement desirable features later if the new technology forces a reduction in the scope of the product, but a minimum feature set should always be maintained.

    如果新技术要求必须削减产品的特性范围,那么您可以在日后再实现所需的特性,但最基本的特性集必须要一直保留。

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  • The article introduces the structure feature and working principle of a new type Reduction Sleeves with 7:24 taper and indicates its use value and application prospect.

    介绍一种新型7:24锥柄用过渡套的结构特点和工作原理,并提出了其使用价值和应用前景。

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  • Based on resolution reduction, neural network is then utilized for feature compression, which can effectively reduce the dimension of features.

    在降低图像解析度的基础上使用神经网络来进行特征压缩,可以有效地降低特征维数。

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  • 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。

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  • Feature selection and input dimension reduction are of Paramount im-portance to transient stability assessment based on neural networks.

    输入特征选择和输入空间降维是基于神经网络暂态稳定评估的首要问题。

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  • This paper presents the principle, feature and effect of fast reduction of ammonia catalyst and points of attention to be paid in the application of fast reduction.

    介绍氨催化剂快速还原的原理、特点及效果,提出应用快速还原法应注意的问题。

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  • This paper proposes two new methods: feature weighted likelihood and divergence based dimension reduction to improve detecting performance in noise.

    本文提出了两种特征处理方法:特征的似然度加权和基于散度的维数缩减,来提高噪声下端点检测的性能。

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  • Margin maximization feature weighting is an effective dimension reduction technique, and it is generally based on weighting techniques and similarity measure to construct their objective functions.

    间距最大化特征选择技术是一种有效的维数约减技术,一般是基于加权技术和相似性度量构造目标函数。

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  • Data pre-processing, data reduction, feature selection, and feature transformation.

    数据预处理,数据压缩,特征选择与特征变换。

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  • In the domain of information retrieval, using feature clustering to extract the features is one of the most important means in the reduction of text dimension.

    借助特征聚类进行特征抽取是信息检索领域进行文本特征降维的重要手段之一。

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  • Micronized coal reburning and air staging are two kinds of typical in-furnace NO_x reduction technologies with advantages of high NO_x reduction efficiency and cost effective feature.

    超细煤粉再燃和空气分级是两种典型的炉内燃烧脱硝技术,具有脱硝率较高,经济性较好的特点。

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  • Then a feature based polyhedral model is reconstructed adaptively, so a large scale precise data reduction, under allowable error, is also realized at the same time.

    在此基础上,完成了基于特征的曲面网格自适应构造,实现了大规模点云的精确数据压缩。

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  • The order is a regular state that can be recognized by the human mind and make human happy. It has the feature of cost-reduction, easy-controlling, and expeetablity.

    秩序是人的心智模式可以识别的、令人感到愉悦的规则状态,它具有成本的节约性、可控性和可预期性等特征。

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  • Feature space is high dimensional and sparse in text categorization, the process of dimension reduction is a very key problem for large-scale text categorization.

    文本分类中特征向量空间是高维和稀疏的,降维处理是分类的关键步骤。

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  • Feature: Auto Focus, Carl Zeiss Optics, Flash, Red-Eye Reduction, Self Timer, Video Stabilization.

    特写:自动对焦,卡尔·蔡司光学认证,闪光灯,红眼减弱,定时器,视频稳定。

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  • The author gains insights from attribute reduction based on discernability matrix and proposes a few rough-set based text feature selection algorithms, i. e. , DB1, DB2 and LDB.

    作者从基于分辨矩阵的粗糙集属性约简中受到启发,提出了一系列基于粗集理论的文本特征选择算法,即DB1、DB2、LDB。

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  • Extended approach three: a hierarchical reduction approach is imported, which is based on the combination of statistical feature selection and linear discriminant analysis.

    拓展算法三:引入统计筛选和线性判别分析相结合的分层递阶约简算法。

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  • Based on a detailed study of these processes, this thesis focuses on characteristics of feature dimension reduction and feature weighting.

    本文在对这些过程进行详细了解和研究的基础之上,重点探讨了特征降维和特征加权过程。

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  • The user feature extraction algorithmic in this paper reference from attribute reduction and decision rule extraction of rough set theory.

    本文中用户行为特征提取算法的设计主要借鉴了粗糙集理论中的属性约简与规则提取的思想。

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  • Dimension reduction techniques were discussed from the two aspects: feature selection and dimension transformation.

    从属性选择和维变换两个方面对维规约技术进行了概括。

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  • Feature dimension reduction can be divided into two categories: feature extraction and feature selection.

    特征降维可以分为两类:特征抽取和特征提取。

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  • Feature dimension reduction can be divided into two categories: feature extraction and feature selection.

    特征降维可以分为两类:特征抽取和特征提取。

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