@@ -97,8 +97,8 @@ def predict(self, X):
9797 Perform uplift on samples in X.
9898
9999 Args:
100- X (array-like, shape (n_samples, n_features)) - Training vector, where n_samples is the number of samples
101- and n_features is the number of features.
100+ X (array-like, shape (n_samples, n_features)): Training vector, where n_samples is the number of samples
101+ and n_features is the number of features.
102102
103103 Returns:
104104 array (shape (n_samples,)): uplift
@@ -208,7 +208,7 @@ def predict(self, X):
208208 Perform uplift on samples in X.
209209
210210 Args:
211- X (array-like, shape (n_samples, n_features)) - Training vector, where n_samples is the number of samples
211+ X (array-like, shape (n_samples, n_features)): Training vector, where n_samples is the number of samples
212212 and n_features is the number of features.
213213
214214 Returns:
@@ -379,8 +379,8 @@ def predict(self, X):
379379 Perform uplift on samples in X.
380380
381381 Args:
382- X (array-like, shape (n_samples, n_features)) - Training vector, where n_samples is the number of samples
383- and n_features is the number of features.
382+ X (array-like, shape (n_samples, n_features)): Training vector, where n_samples is the number of samples
383+ and n_features is the number of features.
384384
385385 Returns:
386386 array (shape (n_samples,)): uplift
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