Comparative Analysis of Statistical Optimizers for Logistic Regression

Logistic regression is one of the method of statistics and closely related to machine learning. Optimization technique plays very important role while building any Machine learning model. This research compares different optimization techniques which can be used for logistic regression; further it talks about which optimization technique can be the best optimization technique among the selected techniques to perform logistic regression based on prediction accuracy and loss obtained during experimental analysis. The obtained results demonstrate that RMSProp works well in practice and compares favorably to other optimization methods.