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MULTI-LEVEL DIMENSIONALITY REDUCTION METHODS USING FEATURE SELECTION AND FEATURE EXTRACTION

机译：基于特征选择和特征提取的多维度降维方法

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Lalitha Rangarajan;
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年度 2010
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专利

1. Multi-Level Dimensionality Reduction Methods Using Feature Selection and Feature Extraction [J] . Veerabhadrappa, Lalitha Rangarajan International Journal of Artificial Intelligence & Applications (IJAIA) . 2010,第4期

机译：使用特征选择和特征提取的多维度降维方法
2. Fast hybrid dimensionality reduction method for classification based on feature selection and grouped feature extraction [J] . Li Mengmeng, Wang Haofeng, Yang Lifang, Expert systems with applications . 2020,第Jula期

机译：基于特征选择和分组特征提取的分类的快速混合维度减少方法
3. Hybrid dimension reduction by integrating feature selection with feature extraction method for text clustering [J] . Kusum Kumari Bharti, Pramod Kumar Singh Expert Systems with Application . 2015,第6期

机译：通过将特征选择与特征提取方法集成来进行文本聚类的混合降维
4. Heuristic Search Algorithm for Dimensionality Reduction Optimally Combining Feature Selection and Feature Extraction [C] . Baokun He, Swair Shah, Crystal Maung, AAAI Conference on Artificial Intelligence . 2019

机译：高维减少的启发式搜索算法最佳地组合特征选择和特征提取
5. New covariance-based feature extraction methods for classification and prediction of high-dimensional data. [D] . Sofolahan, Mopelola A. 2013

机译：基于协方差的新特征提取方法，用于高维数据的分类和预测。
6. A Comparison of Different Dimensionality Reduction and Feature Selection Methods for Single Trial ERP Detection [O] . Tian Lan, Deniz Erdogmus, Lois Black, -1

机译：对于单次ERp检测不同的降维和特征选择方法的比较
7. Bi-level dimensionality reduction methods using feature selection and feature extraction [O] . Lalitha Rangarajan 2011

机译：使用特征选择和特征提取的双层降维方法

MULTI-LEVEL DIMENSIONALITY REDUCTION METHODS USING FEATURE SELECTION AND FEATURE EXTRACTION

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