International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 6 Issue 6
November-December 2024
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Myers-briggs Personality Prediction using Machine Learning Techniques
Author(s) | Ankur Vipin Sheth, Dev Rohit Pandhare |
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Country | India |
Abstract | The Myers-Briggs Type Indicator (MBTI) is a popular and widely used personality assessment tool that categorizes individuals into one of sixteen different personality types based on their preferences for certain psychological traits. This makes MBTI a fascinating subject for research in the fields of psychology and artificial intelligence. Machine learning has advanced significantly in recent years and has become a powerful tool for predicting outcomes based on data. By using machine learning algorithms to analyse data from MBTI tests, researchers can potentially identify patterns and develop models that accurately predict an individual's personality type based on their responses to the test. The ability to predict an individual's personality type could have a range of practical applications, such as in the workplace or in personalized marketing. For example, employers could use personality predictions to build more effective teams, while marketers could use them to tailor advertisements and products to specific personality types. |
Keywords | MBTI |
Field | Computer > Artificial Intelligence / Simulation / Virtual Reality |
Published In | Volume 6, Issue 1, January-February 2024 |
Published On | 2024-01-06 |
Cite This | Myers-briggs Personality Prediction using Machine Learning Techniques - Ankur Vipin Sheth, Dev Rohit Pandhare - IJFMR Volume 6, Issue 1, January-February 2024. DOI 10.36948/ijfmr.2024.v06i01.11660 |
DOI | https://doi.org/10.36948/ijfmr.2024.v06i01.11660 |
Short DOI | https://doi.org/gtdr7k |
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E-ISSN 2582-2160
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