(self, X, Y, Y_all)
| 27 | self.binarizer = MultiLabelBinarizer(sparse_output=True) |
| 28 | |
| 29 | def train(self, X, Y, Y_all): |
| 30 | self.binarizer.fit(Y_all) |
| 31 | X_train = [self.embeddings[x] for x in X] |
| 32 | Y = self.binarizer.transform(Y) |
| 33 | self.clf.fit(X_train, Y) |
| 34 | |
| 35 | def evaluate(self, X, Y): |
| 36 | top_k_list = [len(l) for l in Y] |
no outgoing calls
no test coverage detected