Choosing an Optimal Machine Learning Classifier for Facial Recognition
B. Pavan Vishnu Sai, Pallikonda Raj Sudarshan, C Gunal, Rohit Kumar Gupta · International Journal of Engineering Research in Computer Science and Engineering · 2022
Facial recognition is vital in today's technological world. There is a need to develop facial recognition systems which have high accuracy and at the same time high input to output response. To overcome the problem of low accuracy of facial recognition system we have attempted to combine different algorithm’s and develop a high accuracy facial recognition system. On combining different algorithms, we have observed that the Random Forest classifier achieved 96% accuracy in 2 secs. On the other hand, the Linear Discriminant Analysis classifier achieved 97% in 0 secs. Here we will compare the 6 classifiers to choose a optimal classifier.