Abstract:
There are many diseases in Bangladesh where diabetes is ordinary disease of human body.
A human is affected when his body sugar level over a period is pretty much high. It also
causes of stroke, heart attack, kidney failure and blindness etc. It is possible to control if
you understand the earlier stage and can save a human life. This is a disease which is in
growing day by day. The motive of this study to do the measurement of the performances
of some popular Machine Learning algorithms. In recent years, Machine Learning is a
wonderful platform which has a huge impact on different corner of science and technology
including medical sectors. There are many algorithms in Machine Learning. But in this
paper work, we have used five popular ML algorithms which is Gaussian Naïve Bayes,
Random Forest, Support Vector Machine, Logistic Regression and Decision Tree to find
out the measurement of performances. These algorithms have been trained and tested on
real data for diabetes patients in Bangladesh. The performances of these techniques are
enlisted. We have used diabetes patient dataset, conducted in 2021, derived from Islami
Bank Hospital and Diagnostic Center. The dataset consists of 485 data which contains 267
true class and the rest of data is false class. When we applied algorithms then we find that
Random Forest based algorithm gives 97% accuracy. So, the RF based classifier is better
than other algorithms.
