Train Travel Experience Project

Goal:
The goal of the problem is to predict whether a passenger was satisfied or not considering his/her overall experience of traveling on the Shinkansen Bullet Train.

Dataset: 

The problem consists of 2 separate datasets: Travel data & Survey data. Travel data has information related to passengers and attributes related to the Shinkansen train, in which they traveled. The survey data is aggregated data of surveys indicating the post-service experience. You are expected to treat both these datasets as raw data and perform any necessary data cleaning/validation steps as required.

 

The data has been split into two groups and provided in the Dataset folder. The folder contains both train and test data separately.

• Train_Data

• Test_Data

 

Target Variable:

Overall_Experience (1 represents ‘satisfied’, and 0 represents ‘not satisfied’)

​

Data Dictionary:

All the data is self-explanatory. The survey levels are explained in the Data Dictionary file.

​

Summary:

Artificial neural network that utilized batch normalization, leaky ReLU, and dropout layers allowed for loss to minimize and accuracy to rise to 92%. 

​

​

​

​

​

​

​

​

​

​

​

​