The importance of classifying cancer patients into high to low-risk groups has led many research teams to study the application of machine learning (ML) methods. Here, the leukemia dataset is used for classification to diagnosis the disease. The proposed K-Watts classifying algorithm, compared to other classification algorithms, yields the lowest error rate. The purpose of the reproduction for record protection is to represent a clear idea about the new Fuzzy Responsibility- Based Access Organizer (FRBAO). The projected reproduction provides the wider society safe plans, or with access to the organized mode in MultiPlan hypothesis, using fuzzy constraints. The view part of RBAO can be modified with inactive and active authorization duty. The records in the database can be allowed to access depends on the constraints. The existing and new records are making to appeal with the updated record. The proposed reproduction deal with the fuzzy approach along with the datasets. The method is based on fuzzy linguistic variables and Communicating Sequential Processes (CSP) with multi-objective fuzzy supervisory production to identify and to aid in the early detection of cancer cells.
Digital Object Identifier (DOI)
Shuriya, B. and Rajendran, A.
"A Fuzzy Responsibility-Based Access Organizer for Leukemia Record Protection using KWatts Algorithm,"
Applied Mathematics & Information Sciences: Vol. 13:
6, Article 19.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol13/iss6/19