Soumayan-pal01/Airline-Passenger-Satisfaction

In this project we have performed a detailed analysis and visualization of the training dataset with different Exploratory Data Analysis techniques. Then a comaparative analysis of different Classifier models have been done to predict the passenegr satisfaction class. After performing the model comparative analysis we can conclude that the Random Forest Classifier and the Support Vector classifier have performed better. HYpertuning on both of these classifiers have been done to reduce overfitting and achieve an improved accuracy of 97.15% and 96.57% respectively.

Jupyter Notebook