Data dimensional reduction and principal components analysis
نویسندگان
چکیده
منابع مشابه
Integrating Data Transformation in Principal Components Analysis.
Principal component analysis (PCA) is a popular dimension reduction method to reduce the complexity and obtain the informative aspects of high-dimensional datasets. When the data distribution is skewed, data transformation is commonly used prior to applying PCA. Such transformation is usually obtained from previous studies, prior knowledge, or trial-and-error. In this work, we develop a model-b...
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ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2019
ISSN: 1877-0509
DOI: 10.1016/j.procs.2019.12.111