Paper Key : IRJ************345
Author: Rahul Ashok Maurya,Shivnath Ramfal Mandal,Manish Rajesh Yadav,Kartikey Arun Pathak
Date Published: 05 Aug 2022
Abstract
Abstract: The project uses Classification Algorithm like K-Mean Clustering, Hierarchical clustering Logistic Regression and Support Vector Machine to mine user characteristics data and learn from the patterns. This project comes where large data of personal behavior is used. This project is useful in identifying personality behavior of a person. Both the algorithms are implemented and simulated using python and the scikit-learn package. After implementation and simulation, it was observed that the performance of the logistic regression is more compared to the Support vector machine in the case of logistic accuracy was 87.11% whereas Support vector machine has shown 72.49%. Therefore, the research proposed that Logistic is better than support vector machine to predict the academic performance of the students.Keywords: Logistic Regression and Support Vector Machine accuracy of prediction, personality test.1. IntroductionThe project is based on identifying the personality of an individual using machine learning algorithms and big 5 models. The personality of a human plays a major role in the success of an organization. Nowadays, many organizations have also started selecting the candidates based on their personality as this increase the success rate of the work because the person is working in what he is good other than what he is not good to do. The Big Five model is also known as the Five-Factor Model (FFM) and OCEAN model was developed in the early 1980s according to many psychological theories. When the statistical analysis is applied to personality survey data, some words which describes the personality of a person and these words give a idea of the overall character or personality of the person accurately. In this project, two Supervised Algorithm i.e., Logistic Regression and Support Vector Machine is used to predict personality of a person.