کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4960534 1446501 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Partial Least-Squares Method for Three-Mode Three-Way Datasets Based on Tucker Model
ترجمه فارسی عنوان
روش کمترین مربعات برای مجموعه داده های سهبعدی سهطرفه بر اساس مدل تاکر
کلمات کلیدی
کمترین مربعات جایگزین، کاهش ابعادی، مدل رگرسیون خطی،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر علوم کامپیوتر (عمومی)
چکیده انگلیسی

When analyzing two three-mode three-way datasets (object × variable × condition), the objective is to obtain common factors that show the relationships between the two datasets. The partial least-squares (PLS) method has been applied to such datasets to investigate the common factors. However, the PLS method was proposed for two-mode two-way datasets, such as multivariate datasets. Therefore, this method does not consider the condition when searching for relationships between datasets; that is, it tends to regard the same variable under different conditions as different variables. To address this problem, we extended the PLS method to three-mode three-way datasets by using the Tucker model so that the same variable under different conditions is regarded as the same. Moreover, we can apply the proposed method to three-mode three-way datasets with different dimensions for the conditions and variables, and the output is obtained in the form of three-mode three-way datasets. We show the advantage of the proposed method by applying it to a multicollinearity case as a numerical example.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Procedia Computer Science - Volume 114, 2017, Pages 234-241
نویسندگان
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