This project requires one to understand what mode of transport employees prefers to commute to their office. The attached dataset Cars.csv includes employee information about their mode of transport as well as their personal and professional details like age, salary, work exp. We need to predict whether or not an employee will use Car as a mode of transport. Also, which variables are a significant predictor behind this decision?
Perform Exploratory Data Analysis on the dataset Illustrate the insights based on EDA Multicollinearity check and summarization of problem statement for business stakeholders
Prepare the data for analysis
Create multiple models and explore how each model perform using appropriate model performance metrics KNN Naive Bayes (is it applicable here? comment and if it is not applicable, how can you build an NB model in this case?) Logistic Regression Apply both bagging and boosting modelling procedures to create 2 models and compare its accuracy with the best model of the above step. Actionable Insights & Recommendations Summarize your findings from the exercise in a concise yet actionable note