130cbadff294b686e466d430f26b2d069f6bbf59,metric_learn/sdml.py,_BaseSDML,_fit,#_BaseSDML#Any#Any#,65
Before Change
type_of_inputs="tuples")
// set up (the inverse of) the prior M
if self.use_cov:
X = np.vstack({tuple(row) for row in pairs.reshape(-1, pairs.shape[2])})
prior_inv = np.atleast_2d(np.cov(X, rowvar=False))
else:
prior_inv = np.identity(pairs.shape[2])
diff = pairs[:, 0] - pairs[:, 1]
loss_matrix = (diff.T * y).dot(diff)
emp_cov = prior_inv + self.balance_param * loss_matrix
After Change
prior = "identity"
else:
prior = self.prior
_, prior_inv = _initialize_metric_mahalanobis(pairs, prior,
return_inverse=True,
strict_pd=True,
matrix_name="prior")
diff = pairs[:, 0] - pairs[:, 1]
loss_matrix = (diff.T * y).dot(diff)
emp_cov = prior_inv + self.balance_param * loss_matrix
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 3
Instances
Project Name: metric-learn/metric-learn
Commit Name: 130cbadff294b686e466d430f26b2d069f6bbf59
Time: 2019-06-07
Author: 31916524+wdevazelhes@users.noreply.github.com
File Name: metric_learn/sdml.py
Class Name: _BaseSDML
Method Name: _fit
Project Name: metric-learn/metric-learn
Commit Name: 130cbadff294b686e466d430f26b2d069f6bbf59
Time: 2019-06-07
Author: 31916524+wdevazelhes@users.noreply.github.com
File Name: metric_learn/lsml.py
Class Name: _BaseLSML
Method Name: _fit
Project Name: metric-learn/metric-learn
Commit Name: 130cbadff294b686e466d430f26b2d069f6bbf59
Time: 2019-06-07
Author: 31916524+wdevazelhes@users.noreply.github.com
File Name: metric_learn/itml.py
Class Name: _BaseITML
Method Name: _fit