<ul><li>This error occurs because your test data contains categories that weren’t present in the training data.</li><li>One-hot encoding is a method used to convert categorical variables into a format that can be provided to machine learning algorithms.</li><li>One-Hot Encoding transforms each category of a feature into a binary column (0 or 1).</li><li>handle_unknown=’ignore’ can be used in OneHotEncoder from scikit-learn to handle unseen categories gracefully.</li></ul>

How to Handle Unseen Data with One-Hot Encoding in Machine Learning

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