2017-18

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Disease prediction using SVM and Machine Learning
(2018-09-05T11:26:53Z) Divya, Balaji; Deekshita, S; S, Harshita
Disease prediction is of critical importance with respect to advancements in health-car e as well as technology. With the advent of big data and analytics, it has become feasible to develop methods to diagnose and predict diseases in cost effective ways. However, the accuracy of analysis is decreased when the nature of medical data is incomplete. Furthermore, different regions exhibit distinctive characteristics of certain regional diseases, which have the probability to weaken the prediction of disease outbreaks. Thus, there lies a need to establish effective methods by which the predicted values can be separated for successful prediction. The predicted values are such that 0 denotes absence and 1 denotes presence, which is again used to check model performance. An algorithm in python is used to conduct this classification. 1