Navie-generated code change

solution.xml

<changeset>
<change>
<file change-number-for-this-file="1">sklearn/preprocessing/_encoders.py</file>
<original line-count="14" no-ellipsis="true"><![CDATA[
        for i in range(n_features):
            Xi = X[:, i]
            diff, valid_mask = _encode_check_unknown(Xi, self.categories_[i],
                                                     return_mask=True)

            if not np.all(valid_mask):
                if handle_unknown == 'error':
                    msg = ("Found unknown categories {0} in column {1}"
                           " during transform".format(diff, i))
                    raise ValueError(msg)
                else:
                    # Set the problematic rows to an acceptable value and
                    # continue `The rows are marked `X_mask` and will be
                    # removed later.
                    X_mask[:, i] = valid_mask
                    Xi = Xi.copy()
                    Xi[~valid_mask] = self.categories_[i][0]
]]></original>
<modified no-ellipsis="true"><![CDATA[
        for i in range(n_features):
            Xi = X[:, i]
            diff, valid_mask = _encode_check_unknown(Xi, self.categories_[i],
                                                     return_mask=True)

            if not np.all(valid_mask):
                if handle_unknown == 'error':
                    msg = ("Found unknown categories {0} in column {1}"
                           " during transform".format(diff, i))
                    raise ValueError(msg)
                else:
                    # Set the problematic rows to an acceptable value and
                    # continue `The rows are marked `X_mask` and will be
                    # removed later.
                    X_mask[:, i] = valid_mask
                    Xi = Xi.copy()
                    if np.issubdtype(Xi.dtype, np.str_) and len(self.categories_[i][0]) > len(Xi[~valid_mask][0]):
                        Xi = Xi.astype(object)
                    Xi[~valid_mask] = self.categories_[i][0]
]]></modified>
</change>
</changeset>