Machine Learning Based Revealing Psychology Destabilization

Abstract

In today’s world, people are experiencing behavioral - and mental illnesses as a consequence of increased stress and pressure in their everyday lives. Anxiety, depression, stress, schizophrenia, and bipolar disorder are just a few instances of mental health issues. Mental disease is accompanied by both physical and emotional symptoms. Based on their actions and thoughts, this study will establish whether or not a person is suffering from mental illness. Panic attacks, sweating, palpitations, sadness, concern, overthinking, mental illness is indicated by symptoms such as delusions and hallucinations, and each symptom represents a different form of mental disorder. Five machine learning methods were utilized for this study: XGBoost, SVM, Logistic Regression, and Decision Tree, KNN. We employed a feature selection strategy that incorporated an additional tree classifier as well as other pre-processing techniques in this work. A machine learning algorithm has been utilized to identify a mental illness based on the symptoms of a patient that use the feature extraction technique.Parameters Recall, Accuracy, Precision, and Fl-score were used to assess the efficacy of machine learning models.