• NAGIREDDY SOWJANYA
• Dr. Kunjam Nageswara Rao
• Dr. G. Sita Ratnam
• Dangety.Sowjanya

Blood pressure is a serious global public health problem that affects every individuals. Elevated blood pressure is a critical medical condition that affects the major organs like brain, kidneys, heart and sometimes causes death. It is one of the unresolved problem in health sectors. The main objective is to identify, classify and analyze blood pressure on real-life data related to blood pressure. Therefore, a multi supervised machine learning techniques like Logistic regression(LR),Naïve Bayes(NB) and Support Vector Machine(SVM) have been implemented to build a proposed model. Initially, data has been collected from individuals and is pre-processed. Then features are extracted and dataset is loaded into the model to identify, classify and analyze blood pressure. Finally, data visualization is done using bar graphs. Hence, the classification and analysis is done on dataset, SVM algorithm fulfilled highest accuracy of 96.8% when compared with the remaining LR,NB algorithms.

: Blood Pressure(BP), Systolic, Diastolic, Bioinformatics, Machine Learning, Bar graphs, Python, Anaconda Jupyter Notebook, Support Vector Machine(SVM), Naive Bayes(NB) and Logistic Regression(LR).

"CLASSIFICATION AND ANALYSIS OF BLOOD PRESSURE USING MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 11, page no.b631-b636, November-2021, Available :http://www.jetir.org/papers/JETIR2111177.pdf

"CLASSIFICATION AND ANALYSIS OF BLOOD PRESSURE USING MACHINE LEARNING TECHNIQUES", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 11, page no. ppb631-b636, November-2021, Available at : http://www.jetir.org/papers/JETIR2111177.pdf