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What techniques can be used to handle categorical columns in a dataset that have been ordinal encoded?
Ordinal encoding is a technique used to represent categorical data as numerical values. It assigns a unique integer value to each category based on its order or rank within the dataset. For instance, if we have a column representing educational degrees with categories like "High School", "Bachelor's", and "Master's", we can assign values 1, 2, and 3 to these categories respectively.
Once the categorical columns are ordinal encoded, we can use various techniques for handling them, depending on the problem we are trying to solve. Here are some common techniques:
In summary, ordinal encoding is a useful technique for representing categorical data as numerical values. We can use various techniques like scaling, one-hot encoding, feature engineering, and model-based techniques to handle ordinal encoded columns depending on the problem we are trying to solve.
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