Machine Learning -2

Predicting-Employees-Preferred-Mode-of-Transport-

Analyze the data of ABC consulting company, build a predictive model based on the parameters like age, salary, work experience and predict the preferred mode of transport.

Objective

The objective is to build various Machine Learning models on this data set and based on the accuracy metrics decide which model is to be finalized for finally predicting the mode of transport chosen by the employee.

Skills & Tools Covered

• EDA
• Data Preprocessing
• Bagging Classifier (Bagging and Random Forest)
• Boosting Classifier (AdaBoost
• Gradient Boosting
• XGBoost)
• Hyperparameter Tuning using GridSearchCV

Insights:

• We could see that employees who are at lesser distance from Home to Office prefer Public Transport than employees who are farther away, who prefer Private Transport
• Employees who have higher experience, in turn has more salary prefer to travel more through their own/private transport rather than taking public transport
• We have high positive correlation between Age, Work Experience and Salary variables, which in turn is in positive relationship with predictor variable.
• We also see that male employees have license and female employees seem to use Public Transport, as they don’t have license