Review paper on Outlier Detection using Machine Learning Technique
Keywords:
Outlier Detection (OD), Data Mining, Machine Learning (ML)Abstract
OD is a Data Mining Application. Anomaly contains boisterous information which is explored in different areas. The different strategies are now being explored that is more conventional. We reviewed on different procedures and uses of OD that gives an original methodology that is more helpful for the novices. Machine learning methods are widely used for prediction and classification tasks in medical diagnosis. The classification of a disease with greater precision and efficiency for disease diagnosis are the goals of ML methods. The life support equipment and systems for patients are expanding gradually. Human life expectancy rises as a result of this growth. Yet, these medical care frameworks face the few difficulties and issues like deceiving patients' data, protection of information, absence of exact information, absence of medico data, classifiers for expectation and some more. Numerous disease diagnosis and prediction systems, including expert systems, clinical prediction systems, decision support systems, and personal health record systems, have been developed to address these issues. The objective of the proposed system is to assist physicians in making accurate diagnoses of heart and diabetes conditions.
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