2020
DOI: 10.3390/computers9010013
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On Granular Rough Computing: Handling Missing Values by Means of Homogeneous Granulation

Abstract: This paper is a continuation of works based on a previously developed new granulation method-homogeneous granulation. The most important new feature of this method compared to our previous ones is that there is no need to estimate optimal parameters. Approximation parameters are selected dynamically depending on the degree of homogeneity of decision classes. This makes the method fast and simple, which is an undoubted advantage despite the fact that it gives a slightly lower level of approximation to our other… Show more

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“…This particular technique is called standard granulation and was proposed in [24]. The initial work was extended later in many variants and contexts-see [25,26], Polkowski [27,28], Polkowski and Artiemjew [29,30]. These methods, among others, have found application in classification processes [31], data approximations [30], missing values absorbtion [26,29], and, in the recent work, these were used as a key component of the new Ensemble model-see [32].…”
Section: Introductionmentioning
confidence: 99%
“…This particular technique is called standard granulation and was proposed in [24]. The initial work was extended later in many variants and contexts-see [25,26], Polkowski [27,28], Polkowski and Artiemjew [29,30]. These methods, among others, have found application in classification processes [31], data approximations [30], missing values absorbtion [26,29], and, in the recent work, these were used as a key component of the new Ensemble model-see [32].…”
Section: Introductionmentioning
confidence: 99%