An Improved Disease Prediction System Using Machine Learning
DOI:
https://doi.org/10.26438/ijcse/v6i4.8185Keywords:
Support vector machine (SVM), Random Forest(RF)Abstract
There are lots of disease evolving currently due to change in lifestyle, food habits and sleeping habits and there is a lack of technology to identity these. Disease identification using manual checkups is an accurate way but it consumes a lot of time so we need an alternative that performs diseases diagnosis quick and accurate, this leads to need for data analytics and machine learning. Data analytics we analyze the user data and provide insights to the user. We use machine learning techniques to analyze user data and supervised algorithm such as SVM and unsupervised algorithm such as K-Means clustering are used for classification of the datasets .Random forest is used to create decision trees using user data and important data can be extracted from the decision tree.
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