• Mr. Padmalaya Archith.
• Mr. Sirigiri Shiva Sai.
• Ms. Snigdha Neela.
• Mrs. N. Naga Lakshmi.

Personality is a crucial factor since it distinguishes one person from another. Personality prediction has numerous uses in the real world. The main goal of this project is to collect the user's textual data and apply a trained machine learning model to predict his four personality traits: Introversion vs Extroversion, Sensing vs Intuition, thinking vs Feeling, and Judging vs Perceiving. The main goal is to create an application that allows users to answer questions that are then processed and evaluated to determine his personality features. The result is a four-character string in which each character represents a different personality feature; a total of sixteen personality types are possible. The text is classified using the machine learning algorithm Random Forest Classifier, which produces four personality traits. Natural Language Processing (NLP) approaches with the help of NLTK libraries will be used to process and categorize enormous amounts of textual data. Hyper parameter tuning and cross fold validation are used to improve the performance of the model.

ANALYSIS OF HUMAN TRAITS USING MACHINE LEARNING

"ANALYSIS OF HUMAN TRAITS USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.f43-f47, May-2022, Available :http://www.jetir.org/papers/JETIR2205606.pdf

"ANALYSIS OF HUMAN TRAITS USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppf43-f47, May-2022, Available at : http://www.jetir.org/papers/JETIR2205606.pdf