Here I developed a machine learning model for predicting personality traits. It analyzes personal behavior data and uses algorithms like KNN, Logistic Regression, Decision Tree to classify individuals based on traits. It automates the personality assessment process, providing insights for social media, advertising, and recruitment.
The Big Five Factors are:
- Openness to Experience.
- Agreeableness
- Extraversion
- Neuroticism
- Conscientiousness
Proposed Methodology
To solve the problems of the current system, an automated personality categorization system is developed, which employs data mining techniques and machine learning algorithms to categorize the personalities of various users. Also, techniques such as the Big Five Personality Model, Logistic Regression, Decision Tree, Support Vector Machine, KNN, Naïve bais are used. By detecting historical data and patterns, it is simple to identify a person's personality using new techniques, hence defeating the old system. Each candidate must complete the test. It has several questions, and the user must complete it to determine the Big five personality traits. After completing the survey, the user will be able to know his or her personality. This is useful in a variety of fields such as interviews, recruiting processes, government sectors etc if a user's results are acceptable. He or she can work in any organization that is based on personality type occupations. In this system, we determine each user's personality. The personality type is predicted based on the answers given by the user in the personality test. Users who have their personality type predicted can simply apply for jobs and learn about their personality type. Students can also learn about their personalities and compete in competitive exams in the same way.
System Architecture
The system architecture provides an overview of the system's operation. The system's operation begins with the acquisition of data, which is then divided into training and testing data by selecting qualities. The relevant data is then pre-processed to remove duplicate and incorrect data. There are several questions, the user must answer all the questions. Algorithms are applied based on the responses, and the model is trained using the training data. Here we are using big five personality traits and then classify the personality type. Accuracy is measured by testing the system using testing data. So, after that Personality is predicted.
Results and Discussion PERFORMANCE METRICS Evaluation of machine learning algorithms for project is critical. To forecast the personality system, we employed machine learning algorithms such as Linear Regression, KNN, MLP, Random Forest, Naïve Bais, Logistic Regression Decision Tree and many other methods. For predicting behaviour from test data, we have 7 qualities and one attribute labelled as personality. Gender, age, openness, agreeableness, extraversion, neuroticism or emotional stability, and conscientiousness are some of the attributes employed in this method. In our system, we used Five Personality Traits and produced performance measures for each trait. Accuracy were calculated for each attribute.
