Handwriting Analysis for Classification of Human Personality
Bipin Nair B J, K S Koushik, Ankitha Suraj, K. Nithya, Pranav Venkitesan · 2024
This paper explores handwriting analysis for personality classification, leveraging machine learning algorithms like KNN, SVM, Naive Bayes, Decision Trees, and Random Forest. We have Extracted features such as stroke pressure, letter size, slant, and spacing from a diverse dataset, the study compares algorithm performance, showing promising results in accuracy, precision, recall, and F1-score. Implications for psychology, machine learning, and handwriting analysis are discussed. In our study, the results show that models such as SVM achieved over 95% accuracy, followed closely by KNN with more than 94% accuracy, indicating significant progress in data analysis and Classification modeling.