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。
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。
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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