Transform each categorical value into an integer value, which may lead to an arbitrary ordering of categories and potentially mislead the model.

Encode the categorical variables into a vector of boolean values, which could result in an excessively sparse and high-dimensional representation.

Use one-hot hash buckets to convert the categorical string data, efficiently managing the dimensionality by representing each unique value as a binary vector.

Apply run-length encoding to convert each categorical value into a string, which is not suitable for non-sequential data and may not capture the categorical nature effectively.