Bayes Rule in Python
In this exercise you will undertake a practical example of setting up Bayes formula, obtaining new evidence and updating your 'beliefs' in order to get a more accurate result. The example will relate to the likelihood that someone will close their account for your online software product.
These are the probabilities we know:
- 7% (0.07) of people are likely to close their account next month
- 15% (0.15) of people with accounts are unhappy with your product (you don't know who though!)
- 35% (0.35) of people who are likely to close their account are unhappy with your product
Deze oefening maakt deel uit van de cursus
Hyperparameter Tuning in Python
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Assign probabilities to variables
p_unhappy = ____
p_unhappy_close = ____