Paper Title

Personality classification using data Mining

Article Identifiers

Registration ID: IJNRD_194835

Published ID: IJNRD2305262

DOI: Click Here to Get

Authors

Salomi Pawar , Sakshi Panchal , Madhavi Kad

Keywords

—personality classification and prediction, Random forest, SVM, decision tree, logistic regression, KNN, frequent patterns

Abstract

Personality of a person decides whether he can play the role of leader, influence people around, mastering communication skills, do collaborative work, able to do negotiation is business and handle stress. This project deals with the areas wherever it determines the characteristics of someone based on the frequent patterns observed. Personality classification refers to the psychological classification of different types of individuals. The analysis is done using vast set of data in dataset and is being compared with the user input. In this project, the classification of personalities will be done on the basis of these specific characteristics; conscientiousness, openness, extroversion, agreeableness, neuroticism. Researchers have utilised social media data for auto predicting personality. However, it is confusing and complex to mine the social media data as the data can be noisy. The paper proposes machine learning techniques using Random Forest, Logistic Regression, Decision Tree, Support Vector Machine, KNN. The process of implementation and obtaining of the result will include certain steps like- Data collection, Attribute selection, Preprocessing of data, Prediction of personality. The type of personality classification and prediction can be used in certain fields like business intelligence, marketing and psychology. Research in prediction and analysis of human being is in great demand these days. Predicting the personality of candidates by this system has made things simple in varied fields like recruitment procedure, medical counselling and likewise. Personality prediction using the questionnaire helps to find out the behavioural features of the individuals taking the survey.

How To Cite

"Personality classification using data Mining", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 5, page no.c467-c471, May-2023, Available :https://ijnrd.org/papers/IJNRD2305262.pdf

Issue

Volume 8 Issue 5, May-2023

Pages : c467-c471

Other Publication Details

Paper Reg. ID: IJNRD_194835

Published Paper Id: IJNRD2305262

Downloads: 000121117

Research Area: Engineering

Country: Pune, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305262.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305262

About Publisher

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

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Call For Paper - Volume 10 | Issue 8 | August 2025

IJNRD is Scholarly open access journals, Peer-reviewed, and Refereed Journals, High Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool), Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) with Open-Access Publications.

INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (IJNRD) aims to explore advances in research pertaining to applied, theoretical and experimental Technological studies. The goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working in and around the world. IJNRD will provide an opportunity for practitioners and educators of engineering field to exchange research evidence, models of best practice and innovative ideas.

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