In machine learning, tabular regression predicts continuous numeric outcomes from structured, row-and-column data. It models relationships between independent features (like age or price) and a target variable (like sales or temperature). Data scientists and analysts use it for forecasting, risk assessment, and trend analysis. Industries like finance, healthcare, and retail benefit from its interpretable, efficient predictions.
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