Personality Prediction Using Deep Learning

Abhishek Rajesh Jain , Dr Sharda A. Chhabria

KNeighborsClassifier (KNN), Support Vector Machine (SVM), Gaussian Naïve Bayes, Doc2vec, Long Short-Term Memory (LSTM).

The attributes which characterize the person such as emotions, behaviour, mind and temperature define a personality of a person. The project aims to determine personality traits on the basis of Big Five Model and which is considered to be the multi-label classification problem. This project covered various machine learning algorithm and also deep learning techniques for training and testing of models. The steps for building the model are collection of data, pre-processing, feature extraction, splitting data, training, testing and implementing the model. The algorithm used in project are KNeighborsClassifier, Support Vector Machine, Gaussian Naïve Bayes, Long Short-Term Memory neural network. This model successfully classify the personality. The results indicate that LSTM performed best after that Gaussian Naïve Bayes, Support Vector Machine, KNeighborsClassifier. As per results, Gaussian Naïve Bayes perform well by achieving accuracy of 87% and precision of 82% before applying Long Short-Term Memory, However The performance of Support Vector Machine after applying Long Short-Term Memory is outstanding by achieving more than 83% precision and accuracy of 80% for different traits.

Published Paper   E-Certificate

"Personality Prediction Using Deep Learning", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.6, Issue 6, page no.168 - 172, June-2021, Available :https://ijsdr.org/papers/IJSDR2106025.pdf

Volume 6 Issue 6, June-2021

Pages : 168 - 172

Paper Reg. ID: IJSDR_193405

Published Paper Id: IJSDR2106025

Downloads: 000347050

Research Area: Engineering

Country: Akola, Maharashtra, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2106025

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2106025

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition