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Add random seed to MatrixTrainSet #202

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Merged
qtuantruong merged 2 commits into from
Aug 5, 2019
Merged

Add random seed to MatrixTrainSet #202

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a23959c
Add random seed to trainset
qtuantruong Aug 5, 2019
9cc2e89
Fix typos in docs
qtuantruong Aug 5, 2019
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9 changes: 6 additions & 3 deletions cornac/data/trainset.py
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Original file line number Diff line number Diff line change
Expand Up @@ -110,7 +110,7 @@ class MatrixTrainSet(TrainSet):
The dictionary containing mapping from original ids to mapped ids of items.

seed: int, optional, default: None
Random seed for reproduce data sampling.
Random seed for reproducing data sampling.

"""

Expand Down Expand Up @@ -179,7 +179,7 @@ def item_ppl_rank(self):

@classmethod
def from_uir(cls, data, global_uid_map=None, global_iid_map=None,
global_ui_set=None, verbose=False):
global_ui_set=None, seed=None, verbose=False):
"""Constructing TrainSet from triplet data.

Parameters
Expand All @@ -196,6 +196,9 @@ def from_uir(cls, data, global_uid_map=None, global_iid_map=None,
global_ui_set: :obj:`set`, optional, default: None
The global set of tuples (user, item). This helps avoiding duplicate observations.

seed: int, optional, default: None
Random seed for reproducing data sampling.

verbose: bool, default: False
The verbosity flag.

Expand Down Expand Up @@ -258,7 +261,7 @@ def from_uir(cls, data, global_uid_map=None, global_iid_map=None,
print('Min rating = {:.1f}'.format(min_rating))
print('Global mean = {:.1f}'.format(global_mean))

return cls(uir_tuple, max_rating, min_rating, global_mean, uid_map, iid_map)
return cls(uir_tuple, max_rating, min_rating, global_mean, uid_map, iid_map, seed=seed)

def num_batches(self, batch_size):
return estimate_batches(len(self.uir_tuple[0]), batch_size)
Expand Down
2 changes: 1 addition & 1 deletion cornac/eval_methods/base_method.py
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Original file line number Diff line number Diff line change
Expand Up @@ -192,7 +192,7 @@ def _build_uir(self, train_data, test_data, val_data=None):
if self.verbose:
print('Building training set')
self.train_set = MultimodalTrainSet.from_uir(
train_data, self.global_uid_map, self.global_iid_map, global_ui_set, self.verbose)
train_data, self.global_uid_map, self.global_iid_map, global_ui_set, self.seed, self.verbose)

if self.verbose:
print('Building test set')
Expand Down