- pip install recommendation_system
from recommendation_system import complete_recommendation_table
import pandas as pd
Y_df = pd.DataFrame({'Bob': [5, '?', 4], 'Cathy': [5, 4, '?'], \
'Dave' : [2, 5, 5]}, index=['Toy Story', \
'Despicble Me', 'Spiderman'])
output = complete_recommendation_table(Y_df, len(Y_df) + 1, \
unknown='?', max_value=5, min_value=0, regularization_coeff=0.2)
print(output)
- Assume an input table that looks like this:
- |Movie /User | Bob | Cathy | Dave |
- | Toy Story | 5 | 5 | 2 |
- | Despicble Me | ? | 4 | 5 |
- | Spiderman | 4 | ? | 5 |
- The output after filling in the '?' would look something like this:
- |Movie /User | Bob | Cathy | Dave |
- | Toy Story | 4.808920 | 4.917348 | 2.118293 |
- | Despicble Me | 3.998761 | 3.874179 | 4.816824 |
- | Spiderman | 3.818917 | 3.744278 | 4.857076 |
- The function 'complete_recommendation_table' fills all unknown values('?') with the predictions