The paper describes techniques for reducing the dimensionality of attribute space where objects are represented as vectors, tuples and multisets with numerical and/or verbal characteristics. In these tools, many initial attributes are aggregated into a single integral index or several composite indicators with small scales of qualitative estimates. Aggregation of indicators includes various methods for transformation of attributes and their scales. Reducing the dimensionality of attribute space allows us to simplify the solution of applied problems, in particular, problems of multiple criteria choice, and explain the obtained results.
DOI: 10.1088/1742-6596/1801/1/012017
Download PDF from IOPscience: https://iopscience.iop.org/article/10.1088/1742-6596/1801/1/012017
ResearchGate: https://www.researchgate.net/publication/349386795_Techniques_for_reducing_dimensionality_of_attribute_space
Semantic Scholar: https://api.semanticscholar.org/CorpusID:234086518
A. B. Petrovsky. Techniques for reducing dimensionality of attribute space // Journal of Physics: Conference Series, Vol. 1801, № 012017, 2021.