Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing

論文URL:http://dl.acm.org/citation.cfm?doid=3025453.3025912

論文アブストラクト:Datasets which are identical over a number of statistical properties, yet produce dissimilar graphs, are frequently used to illustrate the importance of graphical representations when exploring data. This paper presents a novel method for generating such datasets, along with several examples. Our technique varies from previous approaches in that new datasets are iteratively generated from a seed dataset through random perturbations of individual data points, and can be directed towards a desired outcome through a simulated annealing optimization strategy. Our method has the benefit of being agnostic to the particular statistical properties that are to remain constant between the datasets, and allows for control over the graphical appearance of resulting output.

日本語のまとめ:

グラフ表示の重要性を示すのに使われるのがAnscombe’sQuartet(アンスコムの四つ組み)。散布図はまるっきり違うのに、平均・標準偏差・相関係数が一緒になってしまう例。こうしたデータセットを作り出すためのシステムを、焼きなまし法アルゴリズムで実現。

(128文字)

発表スライド: