Paper Title
Psycometric Check-Up

Abstract
In human life mental emotions play an extremely prominent role. Nowadays, mental health is important as the physical health. Due to hectic lifestyle and unbalanced working environment many people are suffering from various mental diseases. Proper treatment and counseling are required for those people who are suffering from depression, stress and anxiety. It is especially important to find proper mental illness of the patient. Because if there is minute mistake it will directly harm to the health of the patient. Mental health plays a prominent role in every phase of life such as childhood to the last of adulthood. According to WHO more than 50% working people are suffering from different mental health situation. So, it’s time to focus on mental health of people. This paper focuses on reasons of worst mental illness as well as identification of problem. Based on various machine learning techniques and several methods of feature extraction, we find a correct detection of mental illnesses. Many different machine algorithms are there such as Support Vector Machine, Random Forest, Decision Tree, etc. They are having different accuracies on the different datasets. Based on the available data, the article gives a discriminative analysis of mental health detection. Keywords - Mental health, Depression Detection, Machine Learning, Logistic Regression, SVM, Random Forest.