A Review on Dimensionality Reduction Techniques
نویسندگان
چکیده
منابع مشابه
Study on Dimensionality Reduction Techniques and Applications
Data is not collected only for data mining. Data accumulates in an unprecedented speed. Data preprocessing is an important part for effective machine learning and data mining. Data mining is discovering interesting knowledge from large amounts of data, which is the integral part of the KDD (Knowledge Discovery in Databases), which is the overall process of converting raw data into useful inform...
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Dimensionality reduction techniques play important roles in the analysis of big data. Traditional dimensionality reduction approaches, such as principle component analysis (PCA) and linear discriminant analysis (LDA), have been studied extensively in the past few decades. However, as the dimensionality of data increases, the computational cost of traditional dimensionality reduction methods gro...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2017
ISSN: 0975-8887
DOI: 10.5120/ijca2017915260