D. Pavithra, Dr.A.N. Jayanthi


 Machine learning is a method of optimizing the performance criterion using the past experience. It builds the mathematical model by using the theory of statistics, as the main task is to infer from the samples provided. The algorithm uses computational methods to get the information directly from the data. They are mainly used in medical diagnosis for making critical decisions, as the data in the medical field is huge and the accuracy of the diagnosis depends on considering the huge data of the patients. ML improves the accuracy of the diagnostic of the disease. It also provides automatic learning techniques for predicting the common patterns from the realistic data. There are different ML algorithms, the appropriate method has to be chosen based on their performance. This paper focuses on the use of different machine learning algorithms like Support Vector Machine, Naïve Bayesian, J48, Random Forest etc. for accurate medical diagnosis.




Machine Learning; Support Vector Machine; Random forest; Naïve Bayesian; Mathematical Model.

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DOI: https://doi.org/10.26483/ijarcs.v9i4.6281


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