Abstract:
Hair symbolizes the beauty of women and men. All
of us are jealous of our hair. We lose hair at a young age due
to some mistakes or irregularities. Lots of men and women all
over the world are suffering from hair falling and the number
of females is suffering growing per year. Genetically, dandruff,
allergy and stress are the major problems for falling hair. We
are doing this research survey for helping people. This study
is representing two things. First of all, we are findings how
many reasons are involved in hair fall. Another thing is we train
our dataset with machine learning algorithms to find out the
accuracy. Machine learning technologies have rapidly evolved to
analyze survey datasets. SVM, Logistic Regression, Naive Bayes,
Decision Tree, Random Forest, K-nearest Neighbor and XGBoost
algorithms for performance comparison. The experimental results
indicated that XGBoost had the best performance, with an
accuracy of 92.62%.
