def _convert_instances_(self, X, Y):
logger.debug("Creating the Dataset")
x1, x2, garbage, y_double, garbage = generate_complete_pairwise_dataset(
X, Y)
del garbage
logger.debug("Finished the Dataset instances {}".format(x1.shape[0]))
return x1, x2, y_double
def _convert_instances_(self, X, Y):
self.logger.debug('Creating the Dataset')
garbage, garbage, x_train, garbage, y_single = generate_complete_pairwise_dataset(
X, Y)
del garbage
assert x_train.shape[1] == self.n_object_features
self.logger.debug('Finished the Dataset with instances {}'.format(
x_train.shape[0]))
return x_train, y_single
def _convert_instances_(self, X, Y):
self.logger.debug("Creating the Dataset")
x1, x2, garbage, garbage, y_single = generate_complete_pairwise_dataset(X, Y)
del garbage
if x1.shape[0] > self.threshold_instances:
indices = self.random_state.choice(
x1.shape[0], self.threshold_instances, replace=False
)
x1 = x1[indices, :]
x2 = x2[indices, :]
y_single = y_single[indices]
self.logger.debug("Finished the Dataset instances {}".format(x1.shape[0]))
return x1, x2, y_single
