Importance of Data Scaling for Predicting Diabetes and Breast Cancer with Naïve Bayes and Back Propagation Neural Network

Issac.P.J.; G R Sridhar

doi:10.36948/ijfmr.2023.v05i05.7035

Importance of Data Scaling for Predicting Diabetes and Breast Cancer with Naïve Bayes and Back Propagation Neural Network

Author(s)	Issac.P.J., G R Sridhar
Country	India
Abstract	Diabetes and Cancer are some of the most common non-communicable diseases causing disability and death. Hence, early detection methods are invaluable for these two. In this research, three different classification techniques are implemented - Back Propagation Neural Network (BPNN), Naïve Bias (NB), and a combination of both algorithms to predict breast cancer and diabetes. The proposed technique is evaluated for different metrics like accuracy, precision, recall, and false positive rate with both scaled data and the original dataset. For diabetes, an accuracy of 88% was obtained in the actual dataset, whereas the scaled dataset has obtained an accuracy of 93.72%. Similarly, for the breast cancer dataset, an accuracy of 91% was obtained in the actual dataset, whereas the scaled dataset has obtained an accuracy of 93.57%. It is concluded that the scaled data provides better performance metrics. Also, the ensemble approach provides better performance metrics than the individual models for both diabetes and breast cancer.
Keywords	Disease Detection, Disease Prediction, Machine Learning, Neural Network, AI, Back Propagation Neural Network (BPNN), Naïve Bias (NB), Ensemble Algorithm, Breast Cancer, Diabetes
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 5, Issue 5, September-October 2023
Published On	2023-09-29
Cite This	Importance of Data Scaling for Predicting Diabetes and Breast Cancer with Naïve Bayes and Back Propagation Neural Network - Issac.P.J., G R Sridhar - IJFMR Volume 5, Issue 5, September-October 2023. DOI 10.36948/ijfmr.2023.v05i05.7035
DOI	https://doi.org/10.36948/ijfmr.2023.v05i05.7035
Short DOI	https://doi.org/gstc78

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Importance of Data Scaling for Predicting Diabetes and Breast Cancer with Naïve Bayes and Back Propagation Neural Network

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