def test_amazon_resume(self):
print datetime.now()
print "Instantiating Sample"
sample = Sample(
"/Users/cptullio/Predicao-de-Links/PredLig/src/data/amazon_resume.txt",
20, (0.5, 0.5))
print datetime.now()
print "Configuring Attributes or Features"
sample.set_attributes_list({
"preferential_attachment": {},
"common_neighbors": {},
"sum_of_neighbors": {}
})
print datetime.now()
print "Rescue the Sample"
sample.get_sample()
print datetime.now()
print "Classifying the data"
table = sample.set_classification_dataset()
print datetime.now()
print "Making Prediction Link"
predictor = LinkPrediction(dataset=table, folds_number=2)
print datetime.now()
print "Applying Classifier"
print predictor.apply_classifier()
pass
def test_amazon_resume(self):
print datetime.now()
print "Instantiating Sample"
sample = Sample("/Users/cptullio/Predicao-de-Links/PredLig/src/data/amazon_resume.txt", 20, (0.5, 0.5))
print datetime.now()
print "Configuring Attributes or Features"
sample.set_attributes_list({"preferential_attachment":{}, "common_neighbors":{}, "sum_of_neighbors":{}})
print datetime.now()
print "Rescue the Sample"
sample.get_sample()
print datetime.now()
print "Classifying the data"
table = sample.set_classification_dataset()
print datetime.now()
print "Making Prediction Link"
predictor = LinkPrediction(dataset = table, folds_number = 2)
print datetime.now()
print "Applying Classifier"
print predictor.apply_classifier()
pass
