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
Questo esercizio fa parte del corso
Hyperparameter Tuning in Python
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
# Assign probabilities to variables
p_unhappy = ____
p_unhappy_close = ____