From 0e534ae65d3fa7b407d535ca4b44c86192f3cd5b Mon Sep 17 00:00:00 2001 From: Aghiles Date: Thu, 21 Mar 2019 15:24:39 +0800 Subject: [PATCH] change in exp --- cornac/experiment/experiment.py | 6 +++--- examples/c2pf_example.py | 10 +++++----- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/cornac/experiment/experiment.py b/cornac/experiment/experiment.py index ce545102a..2ec389598 100644 --- a/cornac/experiment/experiment.py +++ b/cornac/experiment/experiment.py @@ -91,9 +91,9 @@ def run(self): organized_metrics = {'ranking': [], 'rating': []} # Organize metrics into "rating" and "ranking" for efficiency purposes - #for mt in self.metrics: - # organized_metrics[mt.type].append(mt) - # metric_names.append(mt.name) + for mt in self.metrics: + organized_metrics[mt.type].append(mt) + metric_names.append(mt.name) for model in self.models: if self.verbose: diff --git a/examples/c2pf_example.py b/examples/c2pf_example.py index 5947eb51f..1363a8c69 100644 --- a/examples/c2pf_example.py +++ b/examples/c2pf_example.py @@ -10,20 +10,20 @@ from cornac.experiment import Experiment from cornac import metrics from cornac.models import C2PF -import numpy as np +from cornac.datasets import amazon_office as office # Load office ratings and item contexts, see C2PF paper for details ratings = office.load_rating() contexts = office.load_context() -item_graph_module = GraphModule(data=office_context) +item_graph_module = GraphModule(data=contexts) -ratio_split = RatioSplit(data=office_ratings, +ratio_split = RatioSplit(data=ratings, test_size=0.2, rating_threshold=3.5, shuffle=True, exclude_unknowns=True, verbose=True, item_graph=item_graph_module) -rec_c2pf = C2PF(k=100, max_iter=80, variant='c2pf') +c2pf = C2PF(k=100, max_iter=1, variant='c2pf') # Evaluation metrics nDgc = metrics.NDCG(k=-1) @@ -33,6 +33,6 @@ # Instantiate and run your experiment exp = Experiment(eval_method=ratio_split, - models=[rec_c2pf], + models=[c2pf], metrics=[nDgc, mrr, rec, pre]) exp.run()