- Ting-kai Liu, NUID: 001306707
- Xuyang Li, NUID: 001409590
- Xing Dong, NUID: 001718652
The project focused on the basic prediction of the probability that someone will experience financial distress in the next two years by using two models. By evaluating and comparing their performance, we will finally present our decision.
Both Random Forest Model and Logistic Regression are using for predicting the probability that someone will experience financial distress in the next two years
For Random Forest: it will generate a binary result either yes or no.For Logistic Regression: the result will generate a number from 0 to 1.
>train.csv: Dataset for training models
>test.csv: Dataset for using models to make predictions and evaluate models' performance
You can download datasets from [https://www.kaggle.com/c/GiveMeSomeCredit/data?select=cs-training.csv]
How it works:
>The system will ask to provide 10 parameters for prediction.
>With each prediction, the system will form a record by the person.
>The system will offer two results each generated by one of the models we are using.
You will need the correct version of Java and sbt. The template requires:
- Java Software Developer's Kit (SE) 1.8 or higher
- sbt 1.3.4 or higher. To build and run the project: