METADES get index error when predicting testing data. #278
Description
I try to use METADES to predict the testing data, however it shows the index error.
The shape of the data is
X_train.shape = (5040, 192)
X_test.shape = (1260, 192)
Below is the implementation:
pool = [mlp1, mlp2, mlp3, mlp4, mlp5]
mt = METADES(pool)
mt.fit(X_train, y_train)
score = mt.score(X_test, y_test)predict(), predict_proba(), score() works on training data but not testing data too.
Here is the error message:
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
Cell In[525], line 1
----> 1 kk.predict_proba(X_test)
File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\deslib\base.py:643, in BaseDS.predict_proba(self, X)
638 DFP_mask = np.ones(
639 (ind_ds_classifier.size, self.n_classifiers_))
641 ind_ds_original_matrix = ind_disagreement[ind_ds_classifier]
--> 643 proba_ds = self.predict_proba_with_ds(
644 X[ind_ds_original_matrix],
645 base_predictions[
646 ind_ds_original_matrix],
647 base_probabilities[
648 ind_ds_original_matrix],
649 neighbors=neighbors,
650 distances=distances,
651 DFP_mask=DFP_mask)
653 predicted_proba[ind_ds_original_matrix] = proba_ds
655 return predicted_proba
File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\deslib\des\base.py:269, in BaseDES.predict_proba_with_ds(self, query, predictions, probabilities, neighbors, distances, DFP_mask)
262 raise ValueError(
263 'The arrays query and predictions must have the same number'
264 ' of samples. query.shape is {}'
265 'and predictions.shape is {}'.format(query.shape,
266 predictions.shape))
268 if self.needs_proba:
--> 269 competences = self.estimate_competence_from_proba(
270 query,
271 neighbors=neighbors,
272 distances=distances,
273 probabilities=probabilities)
274 else:
275 competences = self.estimate_competence(query,
276 neighbors=neighbors,
277 distances=distances,
278 predictions=predictions)
File ~\AppData\Local\Programs\Python\Python311\Lib\site-packages\deslib\des\meta_des.py:483, in METADES.estimate_competence_from_proba(self, query, neighbors, probabilities, distances)
479 meta_feature_vectors = np.digitize(meta_feature_vectors,
480 np.linspace(0.1, 1, 10))
482 # Get the probability for class 1 (Competent)
--> 483 competences = self.meta_classifier_.predict_proba(
484 meta_feature_vectors)[:, 1]
486 # Reshape the array from 1D [n_samples x n_classifiers]
487 # to 2D [n_samples, n_classifiers]
488 competences = competences.reshape(-1, self.n_classifiers_)
IndexError: index 1 is out of bounds for axis 1 with size 1May I know what is the problem?
Edit 1: Change code snippet to python code snippet