Description
HI all,
I've run libfm in Ubuntu using the dataset detailed below,
Random model run OK,
however when I tried the rest of the models in my list (I followed the models_example.py example provided here), i.e. BPR, TFIDFModel, Popularity, TensorCoFi, ..., an error "ValueError: sample larger than population" is always triggered with every model.
Please, does anyone know what could be the source of this problem? any suggestion?
There are many entries in Internet related with this problem in python, but the answers and potential causes described I think doesn't apply this case, so is unclear for me.
Btw, the dataset size is bigger than 5K rows...
Thanks in advance,
regards,
R.
------------------ test:
python modeltest2.py
user item rating time title
0 1123 0 2 838985046 NameFilm
1 1107 0 1 838985046 NameFilm
2 1107 0 1 838985046 NameFilm
3 1107 0 2 838985046 NameFilm
4 1107 1 1 838985046 NameFilm
0:00:00.083082 Random [0.262394934911661]
0:00:09.887563 BPR (dim=10,iter=15,reg=0.0001,eta=0.001)
Traceback (most recent call last):
File "modeltest2.py", line 57, in
print evaluator.evaluate_model(m, testing, all_items=items,)
File "build/bdist.linux-x86_64/egg/testfm/evaluation/evaluator.py", line 83, in evaluate_model
File "build/bdist.linux-x86_64/egg/testfm/evaluation/evaluator.py", line 30, in partial_measure
File "/usr/lib/python2.7/random.py", line 321, in sample
raise ValueError("sample larger than population")
ValueError: sample larger than population