Data Preprocessing Questions Medium
Label encoding is a technique used in data preprocessing to convert categorical variables into numerical values. It assigns a unique numerical label to each category in a variable. This is particularly useful when dealing with machine learning algorithms that require numerical inputs, as they cannot directly process categorical data.
Label encoding is typically used when the categorical variable has an inherent ordinal relationship, meaning the categories have a specific order or hierarchy. For example, in a variable representing education level (e.g., "high school", "college", "graduate"), label encoding can assign the values 0, 1, and 2 respectively, preserving the order of the categories.
However, it is important to note that label encoding should not be used when there is no ordinal relationship among the categories, as it may introduce unintended patterns or relationships in the data. In such cases, one-hot encoding or other techniques should be considered instead.