A toolbox in symbolic data framework as a statistical learning and data mining solution for symbolic polygonal data analysis. This study is a new approach in data analysis and it was proposed by Silva et al. (2019) <doi:10.1016/j.knosys.2018.08.009>. The package presents the estimation of main descriptive statistical measures, e.g, mean, covariance, variance, correlation and coefficient of variation. In addition, a method to obtain polygonal data from classical data is presented. Empirical probability distribution function based on symbolic polygonal histogram and a regression model with its main measures are presented.
|Author||Wagner Silva [aut, cre, ths], Renata Souza [aut], Francisco Cysneiros [aut]|
|Maintainer||Wagner Silva <[email protected]>|
|Package repository||View on CRAN|
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