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Straightforward Working Principles Behind Modern Data Visualization Approaches
oleh: Jugurta Montalvao, Luiz Miranda, Bernadette Dorizzi
Format: | Article |
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Diterbitkan: | IEEE 2021-01-01 |
Deskripsi
From state-of-the-art visualization algorithms, we distill six working principles which are, by hypothesis, sufficient to produce visual projections qualitatively similar to those obtained with these state-of-the-art algorithms. These working principles are presented through the geometrical reasoning of the classical Multidimensional Scaling algorithm, and their effectiveness is illustrated through a novel straightforward algorithm for data visualization. We show, using several datasets originated from various applications, that our algorithm can produce visual projections qualitatively similar to those obtained with these state-of-the-art algorithms. Besides, under the same motivation (of simplification), the problem of visualizing large datasets is tackled through a companion algorithm which is able to embed new input patterns.