def getPredictions(self):
     if 'predictions' in self.cache:
         return self.cache['predictions']
     U,S,V = self.getSVD()
     predictions = divisi2.reconstruct(U,S,V)
     self.cache['predictions'] = predictions
     return predictions
def test_all_norm():
    matrix = divisi2.network.conceptnet_matrix('en')
    U, S, V = matrix.normalize_all().svd(k=100)
    rec = divisi2.reconstruct(U, S, V)
    correct, total, accuracy = rec.evaluate_assertions('data:eval/usertest_data.pickle')

    print "accuracy =", accuracy
    assert accuracy > 0.7
    return accuracy
Exemple #3
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def test_all_norm():
    matrix = divisi2.network.conceptnet_matrix('en')
    U, S, V = matrix.normalize_all().svd(k=100)
    rec = divisi2.reconstruct(U, S, V)
    correct, total, accuracy = rec.evaluate_assertions(
        'data:eval/usertest_data.pickle')

    print "accuracy =", accuracy
    assert accuracy > 0.7
    return accuracy