Abstract
This article considers the data-mining system based on fuzzy regression modeling, which allows to extract useful previously unknown patterns such as groups of data records, unusual records and dependencies. Using the fuzzy least-squares approach, we describe the estimation of fuzzy linear regression model with LR-type fuzzy parameters. In conclusion, the received theoretical results are used to analyze experimental data.
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