dimensionality reduction
降维：一种数据处理技术
常用释义
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基本释义
- 降维：一种数据处理技术，用于减少数据集中特征的数量，以便更有效地分析和处理数据。通过降维，可以减少计算复杂性、提高模型的训练速度和性能，并且可以帮助发现数据中的隐藏模式和结构。
例句
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1·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。
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2·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。
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3·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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4·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。
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5·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。
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6·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。
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7·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。
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8·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。
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9·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。
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10·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。