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DC Field | Value | Language |
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dc.contributor.author | ARYAL, NIRMAL | - |
dc.date.accessioned | 2023-07-11T05:45:10Z | - |
dc.date.available | 2023-07-11T05:45:10Z | - |
dc.date.issued | 2023-06 | - |
dc.identifier.uri | http://dspace.dtu.ac.in:8080/jspui/handle/repository/19980 | - |
dc.description.abstract | The relevance of personality prediction and its possible advantages are examined in this thesis study. Since it can help us better understand human behaviour and individual characteristics, personality prediction is vital. The study highlights the value of psychological knowledge gathered through personality prediction in variety of industries, including marketing, education, staffing, mental health, and personal growth. Personalized marketing efforts, targeted product suggestions, and specialised learning tactics are all made possible by personality prediction since it allows experiences and services to be tailored to individual preferences. It helps with educated recruiting decisions and improved job fit in the area of human resources. Furthermore, early detection of personality features linked to mental health issues enables prompt assistance and intervention. Using assessment measures, the study compares the effectiveness of different algorithms. The use of several machine learning and deep learning algorithms allows for a thorough examination of personality prediction methods. The algorithms taken into account in this thesis were chosen to reflect a wide range of methodologies, including ensemble techniques, conventional machine learning, and deep learning models. By comparing the outcomes of these algorithms using evaluation criteria, their advantages and disadvantages in personality prediction tasks are highlighted. The research's findings offer insightful information on how various personality prediction algorithms work. This information can assist in the creation of more precise and successful personality prediction models, enabling the use of personality prediction in real-world contexts. The thesis also advances the science of machine learning by demonstrating the strengths and weaknesses of several algorithms in the context of personality prediction. The ethical issues around privacy, accuracy, and appropriate use of personal information in personality prediction must be taken into account, though. This research increases our knowledge of human behaviour by addressing these issues and utilising the potential advantages of personality prediction. It also prepares the way for future improvements in tailored experiences, hiring procedures, mental health assistance, and personal growth. | en_US |
dc.language.iso | en | en_US |
dc.relation.ispartofseries | TD-6518; | - |
dc.subject | PERSONALITY PREDICTION | en_US |
dc.subject | MACHINE LEARNING ALGORITHMS | en_US |
dc.title | PERSONALITY PREDICTION USING VARIOUS MACHINE LEARNING ALGORITHMS | en_US |
dc.type | Thesis | en_US |
Appears in Collections: | M.E./M.Tech. Information Technology |
Files in This Item:
File | Description | Size | Format | |
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NIRMAL ARYAL M.TEch.pdf | 1.62 MB | Adobe PDF | View/Open |
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