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It improves the efficiency of edge-cloud computing by transforming continuous features into discrete ones, so as to meet the requirements of high-quality cloud services. Compared with other discretization methods, the discretization based on rough set has achieved good results in many applications because it can make full use of the known knowledge base without any prior information. However, the equivalence class of rough set is an ordinary set, which is difficult to describe the fuzzy components in the data, and the accuracy is low in some complex data types in big data environment. Therefore, we propose a rough fuzzy model based discretization algorithm (RFMD). Firstly, we use fuzzy<jats:italic>c<\/jats:italic>-means clustering to get the membership of each sample to each category. Then, we fuzzify the equivalence class of rough set by the obtained membership, and establish the fitness function of genetic algorithm based on rough fuzzy model to select the optimal discrete breakpoints on the continuous features. Finally, we compare the proposed method with the discretization algorithm based on rough set, the discretization algorithm based on information entropy, and the discretization algorithm based on chi-square test on remote sensing datasets. The experimental results verify the effectiveness of our method.<\/jats:p>","DOI":"10.1186\/s13677-020-00216-4","type":"journal-article","created":{"date-parts":[[2021,1,18]],"date-time":"2021-01-18T13:04:42Z","timestamp":1610975082000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["Rough fuzzy model based feature discretization in intelligent data preprocess"],"prefix":"10.1186","volume":"10","author":[{"given":"Qiong","family":"Chen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mengxing","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,18]]},"reference":[{"issue":"3","key":"216_CR1","doi-asserted-by":"publisher","first-page":"1657","DOI":"10.1109\/COMST.2017.2705720","volume":"19","author":"T Taleb","year":"2017","unstructured":"Taleb T, Samdanis K, Mada B et al (2017) On multi-access edge computing: a survey of the emerging 5G network edge cloud architecture and orchestration. 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The sponsors had no role in the design, execution, interpretation, or writing of the study. These no potential competing interests in our paper. And all authors have seen the manuscript and approved to submit to your journal. We confirm that the content of the manuscript has not been published or submitted for publication elsewhere.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"5"}}