NDLI: Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices

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Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices

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Scalable Partial Least Squares Regression on Grammar-Compressed Data Matrices

Content Provider	ACM Digital Library
Author	Saigo, Hiroto Tabei, Yasuo Yamanishi, Yoshihiro Puglisi, Simon J.
Abstract	With massive high-dimensional data now commonplace in research and industry, there is a strong and growing demand for more scalable computational techniques for data analysis and knowledge discovery. Key to turning these data into knowledge is the ability to learn statistical models with high interpretability. Current methods for learning statistical models either produce models that are not interpretable or have prohibitive computational costs when applied to massive data. In this paper we address this need by presenting a scalable algorithm for partial least squares regression (PLS), which we call compression-based PLS (cPLS), to learn predictive linear models with a high interpretability from massive high-dimensional data. We propose a novel grammar-compressed representation of data matrices that supports fast row and column access while the data matrix is in a compressed form. The original data matrix is grammar-compressed and then the linear model in PLS is learned on the compressed data matrix, which results in a significant reduction in working space, greatly improving scalability. We experimentally test cPLS on its ability to learn linear models for classification, regression and feature extraction with various massive high-dimensional data, and show that cPLS performs superiorly in terms of prediction accuracy, computational efficiency, and interpretability.
Starting Page	1875
Ending Page	1884
Page Count	10
File Format	PDF
ISBN	9781450342322
DOI	10.1145/2939672.2939864
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-08-13
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Grammar compression Big data Partial least squares regression Large-scale machine learning
Content Type	Text
Resource Type	Article

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