Because these springs are "hot" in the literal sense—often reaching boiling points—they are primarily viewed as natural wonders rather than swimming holes.
In data processing pipelines, categorical deep features can be transformed using One-Hot Encoding to make them interpretable for machine learning algorithms.
Specifically, the variant known internally as the "Hot" series.
