Exploring Scale-Measures of Data Sets

Autor:	Johannes Hirth, Tom Hanika
Rok vydání:	2021
Předmět:	Set (abstract data type) Data set Theoretical computer science Computer science Formal concept analysis Scale (descriptive set theory) Feature scaling Scientific modelling Scaling Block (data storage)
Zdroj:	Formal Concept Analysis ISBN: 9783030778668 ICFCA
DOI:	10.1007/978-3-030-77867-5_17
Popis:	Measurement is a fundamental building block of numerous scientific models and their creation in data driven science. Due to the high complexity and size of modern data sets, it is necessary to develop understandable and efficient scaling methods. A profound theory for scaling data is scale-measures from formal concept analysis. Recent developments indicate that the set of all scale-measures for a given data set constitutes a lattice. In this work we study the properties of said lattice and propose a novel and efficient scale-measure exploration algorithm, motivating multiple applications for (semi-)automatic scaling.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::8e9a1d2fb8d21844bc4c2559c744f269 https://doi.org/10.1007/978-3-030-77867-5_17 Zobrazit plný text záznamu