Python issue about implicit

[tangbufanwei]

model1.recommend(0,user_item_sparse1[0])
THIS IS THE METHOD I FOUND ON GITHUB BUT SEEMS ITS NOT WORKING ON MY SIDE AS WELL.

[benfred]

I think your issue is here:

data_conf = (item_user_sparse1 * alpha_val).astype('double')
model1.fit(data_conf)
model1.recommend(0,user_item_sparse1[0])

The fit methods take a user_item sparse matrix , https://benfred.github.io/implicit/api/models/cpu/als.html#implicit.cpu.als.AlternatingLeastSquares.fit instead of the item_user sparse matrix that you are passing it.

Does calling the fit function with the correct argument work for you?

model1.fit(user_item_sparse1)
model1.recommend(0,user_item_sparse1[0])

[tangbufanwei]

Thank for your reply but i got

several weird arrays, i am not sure if it's correct, but finally it's not red anymore.

[tangbufanwei]

and my sparse matrix looks like this