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Continuous feature: Difference between revisions
Created page with "===Introduction== Machine learning usually divides data into two primary types: continuous and categorical. Continuous features, also referred to as numerical or quantitative features, refer to variables that take on a range of numeric values like age, weight, and height. These features are commonly employed in regression models that aim to predict an output variable such as sales or revenue based on input features. Understanding continuous features is critical for creat..."
(Created page with "===Introduction== Machine learning usually divides data into two primary types: continuous and categorical. Continuous features, also referred to as numerical or quantitative features, refer to variables that take on a range of numeric values like age, weight, and height. These features are commonly employed in regression models that aim to predict an output variable such as sales or revenue based on input features. Understanding continuous features is critical for creat...") |
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