Classical feature extraction methods include: Principle Component Analysis、Singular Value Decomposition、Projection Pursuit、Self-Organizing Map, and so on.
传统的特征提取方法主要有:主分量分析、奇异值分解、投影追踪、自组织映射等。
参考来源 - 模式分类特征提取中的独立分量分析Principle component analysis and multiple regression analysis on principle components have been adopted in a runoff dataset to investigate the relation between runoff characteristic value and instream flow.
采用主成分分析和多元回归相结合的方法确定径流特征值和河流生态环境需水之间的关系。
参考来源 - 南方地区生态环境需水研究·2,447,543篇论文数据，部分数据来源于NoteExpress
The analysis method includes linear regression and principle component analysis.
分析方法包括趋势分析、主分量分析。
Aiming at the preceding problem, this paper puts forward a feature selection method using Information Gain (IG) and Principle Component (Analysis) (PCA).
针对上述问题，提出了信息增益(IG)与主成分分析(PCA)相结合的特征选择方法。
Classical feature extraction methods include: Principle Component Analysis, Singular Value Decomposition, Projection Pursuit, Self-Organizing Map, and so on.
传统的特征提取方法主要有：主分量分析、奇异值分解、投影追踪、自组织映射等。
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