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ABSTRACT
One of the major phenomenon that can easily lead to increased rate of mortality is stress if not early detected, this is due to the many stressors like anxiety, insomnia, high blood pressure and a weakened immune system, which may be triggered by the daily activities in the society. This research study proposes a hybrid machine learning model in the prediction of stress using both the adaptive fuzzy inference system and principle component analysis. The experimental results obtained an accuracy of 98%, Sensitivity of 98.25%, Specificity of 99% and Precision of 98% showing a promising prospect for future improvement.
