Project for Neural Networks course taken in Sapienza University of Rome during an exchange in 2017.
- Project report: PDF
- Practical part: IPython notebook
- Created Algorithms: Tri-Training and Self-Training
Project for Neural Networks course taken in Sapienza University of Rome during an exchange in 2017.
Thank for your program,I try to run it , but I meet the error:
ValueError Traceback (most recent call last)
in
21 test_info = { "classifier": classifier.name, "dataset":dataset_name, "labeling_rate":labeling_rate}
22 cv = KFold(n_splits=10, random_state=42)
---> 23 scores, cnf_matrix = train_and_score(classifier, dataset["X"], dataset["y"], cv, labeling_rate)
24
25 if results is None:
in train_and_score(clf, X, y, cv, labeling_rate)
48 testing_scores = []
49 for training_index, test_index in cv.split(X,y):
---> 50 transductive_score, testing_score, cnf_matrix = _training_scoring_iteration(clf, X, y, training_index, test_index, labeling_rate)
51
52 transductive_scores.append(transductive_score)
in _training_scoring_iteration(clf, X, y, training_index, test_index, labeling_rate)
28
29 #Train the classifier
---> 30 clf.fit(X_train, y_train)
31
32 #Score the classifier
~/tri_training.py in fit(self, X, y)
25 changed = False
26 for t1, t2, t3 in third_rotations:
---> 27 changed |= t1.train(t2, t3, X[unlabeled])
28
29
~/tri_training.py in train(self, t1, t2, unlabeled_X)
76 count_of_added = len(L_X)
77 # Turn the python list of chosen samples into numpy array
---> 78 L_X = np.concatenate(L_X)
79 L_y = np.concatenate(L_y)
80
ValueError: need at least one array to concatenate
If you could help me,I will be grateful :)
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