diff options
Diffstat (limited to 'gensvm')
| -rw-r--r-- | gensvm/core.py (renamed from gensvm/models.py) | 8 |
1 files changed, 4 insertions, 4 deletions
diff --git a/gensvm/models.py b/gensvm/core.py index f06374b..7594eba 100644 --- a/gensvm/models.py +++ b/gensvm/core.py @@ -15,7 +15,7 @@ from sklearn.utils import check_X_y, check_random_state from sklearn.utils.multiclass import type_of_target from sklearn.utils.validation import check_is_fitted -from . import pyx_gensvm +from . import wrapper def _fit_gensvm(X, y, p, lmd, kappa, epsilon, weight_idx, kernel, gamma, coef, @@ -25,10 +25,10 @@ def _fit_gensvm(X, y, p, lmd, kappa, epsilon, weight_idx, kernel, gamma, coef, rnd = check_random_state(random_state) # set the verbosity in GenSVM - pyx_gensvm.set_verbosity_wrap(verbose) + wrapper.set_verbosity_wrap(verbose) # run the actual training - raw_coef_, n_SV_, n_iter_, training_error_, status_ = pyx_gensvm.train_wrap( + raw_coef_, n_SV_, n_iter_, training_error_, status_ = wrapper.train_wrap( X, y, p, lmd, kappa, epsilon, weight_idx, kernel, gamma, coef, degree, kernel_eigen_cutoff, max_iter, rnd.randint(np.iinfo('i').max)) @@ -181,7 +181,7 @@ class GenSVM(BaseEstimator): check_is_fitted(self, "coef_") V = np.vstack((self.intercept_, self.coef_)) - predictions = pyx_gensvm.predict_wrap(X, V) + predictions = wrapper.predict_wrap(X, V) # Transform the classes back to the original form predictions -= 1 |