- Bank Marketing Data Set: UCI, Download
- Write a Jupyter notebook
- load data (
bank.csv
, smaller sample), normalize, and devide training/test sets - randomly select 2 or 3 features
- apply the methods covered in Ch. 3 with SK-learn (logistic regress, SVM, decision tree, etc)
- check the accuracy and plot the outcome
- repeat above to find better feature
- load data (
atomme / phbs_tqfml Goto Github PK
View Code? Open in Web Editor NEWThis project is created for 2017-18 Module 3 (Spring), Topics in Quantitative Finance: Machine Learning for Finance