How to deal with unbalanced dataset in Machine Learning (ML)

 Unbalanced dataset is very common. For example, credit card transaction (majority of them are authentic), malware detection ( majority are benign), internet traffic( majority are friendly), CT-scan ( majority without tumor), etc.

Why we need to deal with it and how to deal with it. Here we are going to use Jupyter notebook to illustrate this problem. 

I am writing this post little by little, so it may takes a few days to finish. 

https://github.com/chaowu2009/ML_Projects/blob/master/ML_unbalanced_data.ipynb

pandas, groupby result to file

 grpd = df.groupby('name').size()

print(grpd)

grpd.reset_index().to_csv('result.csv')