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| author | Rémi Flamary <remi.flamary@gmail.com> | 2020-04-24 11:28:21 +0200 |
|---|---|---|
| committer | Rémi Flamary <remi.flamary@gmail.com> | 2020-04-24 11:28:21 +0200 |
| commit | 6931f78c7e5b1da4f62a1a85d87409f3f95029c7 (patch) | |
| tree | 19900dad3007382a2d6189f07a2b9966e84f7eda /ot/da.py | |
| parent | 8599e720d5f438e2aaf5c635883e64deb026f3ce (diff) | |
better documentation
Diffstat (limited to 'ot/da.py')
| -rw-r--r-- | ot/da.py | 28 |
1 files changed, 14 insertions, 14 deletions
@@ -908,7 +908,8 @@ class BaseTransport(BaseEstimator): at the class level in their ``__init__`` as explicit keyword arguments (no ``*args`` or ``**kwargs``). - fit method should: + the fit method should: + - estimate a cost matrix and store it in a `cost_` attribute - estimate a coupling matrix and store it in a `coupling_` attribute @@ -933,7 +934,7 @@ class BaseTransport(BaseEstimator): Xs : array-like, shape (n_source_samples, n_features) The training input samples. ys : array-like, shape (n_source_samples,) - The class labels + The training class labels Xt : array-like, shape (n_target_samples, n_features) The training input samples. yt : array-like, shape (n_target_samples,) @@ -994,7 +995,7 @@ class BaseTransport(BaseEstimator): Xs : array-like, shape (n_source_samples, n_features) The training input samples. ys : array-like, shape (n_source_samples,) - The class labels + The class labels for training samples Xt : array-like, shape (n_target_samples, n_features) The training input samples. yt : array-like, shape (n_target_samples,) @@ -1018,13 +1019,13 @@ class BaseTransport(BaseEstimator): Parameters ---------- Xs : array-like, shape (n_source_samples, n_features) - The training input samples. + The source input samples. ys : array-like, shape (n_source_samples,) - The class labels + The class labels for source samples Xt : array-like, shape (n_target_samples, n_features) - The training input samples. + The target input samples. yt : array-like, shape (n_target_samples,) - The class labels. If some target samples are unlabeled, fill the + The class labels for target. If some target samples are unlabeled, fill the yt's elements with -1. Warning: Note that, due to this convention -1 cannot be used as a @@ -1085,7 +1086,7 @@ class BaseTransport(BaseEstimator): Parameters ---------- ys : array-like, shape (n_source_samples,) - The class labels + The source class labels Returns ------- @@ -1125,18 +1126,18 @@ class BaseTransport(BaseEstimator): def inverse_transform(self, Xs=None, ys=None, Xt=None, yt=None, batch_size=128): - """Transports target samples Xt onto target samples Xs + """Transports target samples Xt onto source samples Xs Parameters ---------- Xs : array-like, shape (n_source_samples, n_features) - The training input samples. + The source input samples. ys : array-like, shape (n_source_samples,) - The class labels + The source class labels Xt : array-like, shape (n_target_samples, n_features) - The training input samples. + The target input samples. yt : array-like, shape (n_target_samples,) - The class labels. If some target samples are unlabeled, fill the + The target class labels. If some target samples are unlabeled, fill the yt's elements with -1. Warning: Note that, due to this convention -1 cannot be used as a @@ -1227,7 +1228,6 @@ class BaseTransport(BaseEstimator): class LinearTransport(BaseTransport): - """ OT linear operator between empirical distributions The function estimates the optimal linear operator that aligns the two |