what are lable-encoding and one-hot encoding? when to use one over other?

Question

Accepted Answer

Label encoding and one-hot encoding are techniques used to convert categorical data into numerical data.

Label encoding assigns a unique numerical value to each category in a feature.
One-hot encoding creates a binary vector for each category in a feature.
Label encoding is useful when the categories have an inherent order or hierarchy.
One-hot encoding is useful when the categories are unordered or when the number of categories is small.
One-hot encoding can lead to a high-dimensional feature space.
Label encoding can be used for features like education level, where there is a natural ordering.
One-hot encoding can be used for features like color, where there is no natural ordering.

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