def estimate_user(user, rest):
bu = user > 0
br = rest > 0
ws = all_correlations(bu,br)
selected = ws.argsort()[-100:]
estimates = rest[selected].mean(0)
estimates /= (.1+br[selected].mean(0))
return estimates
def estimate_user(user, rest, num_neighbors=100):
'''Estimate ratings for user based on the binary rating matrix
Returns
-------
estimates: ndarray
Returns a rating estimate for each movie
'''
# Compute binary matrix correlations:
bu = user > 0
br = rest > 0
ws = all_correlations(bu, br)
# Select top `num_neighbors`:
selected = ws.argsort()[-num_neighbors:]
# Use these to compute estimates:
estimates = rest[selected].mean(0)
estimates /= (.1 + br[selected].mean(0))
return estimates
