Categorical Features
Explore the definition and types of categorical features, understand challenges such as high cardinality, and learn how to apply encoding methods including one-hot encoding to prepare data effectively for machine learning models. This lesson helps you transform categorical data, improving data quality and model accuracy.
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Categorical features take a fixed or small set of values. Consider the example of Gender (Male, Female) or education of a person (High school, college, masters, Ph.D., etc). Even if the data contains features that have a fixed set of values, we can mark it as a categorical feature. For example, consider the error code in the manufacturing process. We can receive an error code in case of any process failures. This code may belong to a predefined set of values and are qualified as categorical features.