Authors :
Gayatri Tatikonda; Geethika Mannam; Jothsna Bhavani Tirumalasetty
Volume/Issue :
Volume 7 - 2022, Issue 6 - June
Google Scholar :
https://bit.ly/3IIfn9N
Scribd :
https://bit.ly/3u2xhiY
DOI :
https://doi.org/10.5281/zenodo.6736737
Abstract :
Diabetes is a chronic disease that occurs when
the blood sugar levels of a human are high. When we ate,
body turns the food into sugar(glucose). Big Data
Analytics plays important role in the care industries. It
can help in identifying the right treatment for people with
diabetes. Care industries have massive volume of
databases. Kidneys are mainly damaged by the diseases
called diabetes damage, blindness, heart failure. Normally
pancreas is supposed to release insulin. The future
scientific field in the course of data science which deals
with the ways to learn the information from the given
content is Machine Learning. The ways to project the
diabetes in the starting stage in order to control it by
taking the several results obtained by the machine
learning techniques and comparing them with each other
to get the most accurate decision are such as K nearest
neighbor, random forest, decision tree, logistical
regression are used. By using these kind of algorithms we
can calculate the accuracy of the algorithms
Keywords :
Symptoms, Types, Random forest ,Decision tree, Logistic regression, KNN.
Diabetes is a chronic disease that occurs when
the blood sugar levels of a human are high. When we ate,
body turns the food into sugar(glucose). Big Data
Analytics plays important role in the care industries. It
can help in identifying the right treatment for people with
diabetes. Care industries have massive volume of
databases. Kidneys are mainly damaged by the diseases
called diabetes damage, blindness, heart failure. Normally
pancreas is supposed to release insulin. The future
scientific field in the course of data science which deals
with the ways to learn the information from the given
content is Machine Learning. The ways to project the
diabetes in the starting stage in order to control it by
taking the several results obtained by the machine
learning techniques and comparing them with each other
to get the most accurate decision are such as K nearest
neighbor, random forest, decision tree, logistical
regression are used. By using these kind of algorithms we
can calculate the accuracy of the algorithms
Keywords :
Symptoms, Types, Random forest ,Decision tree, Logistic regression, KNN.
