scikit-learn
diff --git a/‎sklearn/linear_model/_stochastic_gradient.py
Copy file name to clipboardExpand all lines: sklearn/linear_model/_stochastic_gradient.py
+3-3Lines changed: 3 additions & 3 deletions b/‎sklearn/linear_model/_stochastic_gradient.py
Copy file name to clipboardExpand all lines: sklearn/linear_model/_stochastic_gradient.py
+3-3Lines changed: 3 additions & 3 deletions
@@ -332,12 +332,12 @@ def loss_function_(self):
         return self._loss_function_
 
 
-def _prepare_fit_binary(est, y, i, input_dtye):
+def _prepare_fit_binary(est, y, i, input_dtype):
     """Initialization for fit_binary.
 
     Returns y, coef, intercept, average_coef, average_intercept.
     """
-    y_i = np.ones(y.shape, dtype=input_dtye, order="C")
+    y_i = np.ones(y.shape, dtype=input_dtype, order="C")
     y_i[y != est.classes_[i]] = -1.0
     average_intercept = 0
     average_coef = None
@@ -432,7 +432,7 @@ def fit_binary(
     # if average is not true, average_coef, and average_intercept will be
     # unused
     y_i, coef, intercept, average_coef, average_intercept = _prepare_fit_binary(
-        est, y, i, input_dtye=X.dtype
+        est, y, i, input_dtype=X.dtype
     )
     assert y_i.shape[0] == y.shape[0] == sample_weight.shape[0]