Shifat Jahan Setu

Work place: Department of Computer Science & Engineering, Jahangirnagar University, Savar, Dhaka-1342, Bangladesh



Research Interests: Data Mining, Machine Learning, Artificial Intelligence


Shifat Jahan Setu completed her M.Sc.  from the Department of Computer Science and Engineering, Jahangirnagar University, Savar, Dhaka, Bangladesh in 2021. She also obtained her B.Sc. degree from the same university in 2019. Currently she is working as a Lecture at the department of Computer Science & Engineering in Dhaka International University (DIU), Dhaka, Bangladesh. Her research interests are Machine Learning, Data Mining and Artificial Intelligence.

Author Articles
Detection of Diabetes using Combined ML Algorithm

By Shifat Jahan Setu Fahima Tabassum Sarwar Jahan Md. Imdadul Islam

DOI:, Pub. Date: 8 Feb. 2024

Recently data clustering algorithm under machine learning are used in ‘real-life data’ to segregate them based on the outcome of a phenomenon. In this paper, diabetes is detected from pathological data of 768 patients using four clustering algorithms: Fuzzy C-Means (FCM), K-means clustering, Fuzzy Inference system (FIS) and Support Vector Machine (SVM). Our main objective is to make binary classification on the data table in a sense that presence or absence of diabetes of a patient. We combined the four machine learning algorithms based on entropy-based probability to enhance accuracy of detection. Before applying combining scheme, we reduce the size of variables applying multiple linear regression (MLR) on the table then logistic regression is again applied on the resultant data to keep the outlier within a narrow range. Finally, entropy based combining scheme with some modification is applied on the four ML algorithms and we got the accuracy of detection about 94% from the combining technique.

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