feat: add features names options for example samples

[Abdoulaye-SAKHO]

No description provided.

[gemini-code-assist]

Code Review

This pull request introduces the ability to specify custom feature_names in the explanation method, updating the documentation and example notebook to demonstrate this new capability. A review comment suggests adding validation to ensure that the length of the provided feature_names matches the number of features in the training data, which would prevent potential runtime errors when constructing the pandas DataFrame.

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[gemini-code-assist]

When feature_names is provided, there is no validation to ensure that its length matches the number of features in the training data (self.train_X.shape[1]). If the lengths do not match, pd.DataFrame will raise a ValueError with an unclear error message. Adding a validation check improves robustness and provides a clear error message to the user.

            if feature_names is None:
                feature_names = [f"feature_{j}" for j in range(self.train_X.shape[1])]
            elif len(feature_names) != self.train_X.shape[1]:
                raise ValueError(
                    f"Length of feature_names ({len(feature_names)}) must match "
                    f"the number of features ({self.train_X.shape[1]})."
                )