jalajthanaki / credit-risk-modelling

Credit Risk analysis by using Python and ML

Credit Risk Modelling

We are building ML model which can help us in order get an idea, whether a person will be doing any default activity for his loan in next 2 year.

Dependency Libraries

• Python 2.7
• pandas
• numpy
• scipy
• scikit-learn
• matplotlib
• seaborn
• jupyter notebook

Installation Commands

I'm working on Linux OS (Ubuntu 16.04 LTS) so command for installating all dependancies are given below.

Pandas:           $ sudo pip install pandas
numpy:            $ sudo pip install numpy
scipy:            $ sudo pip install scipy
scikit-learn:     $ sudo pip install -U scikit-learn
matplotlib: 
                  $ sudo apt-get install libfreetype6-dev libpng-dev
                  $ sudo pip install matplotlib 
seaborn:          $ sudo pip install seaborn
jupyter notebook: $ sudo apt-get -y install ipython ipython-notebook
                  $ sudo -H pip install jupyter

credit-risk-modelling's Issues

Random forest classifier to scorecard

Hi!
It is a great repo!

Is that possible to show, how to convert Random Forest feature importances to a score card?

Thank you!