Feature space is a multidimensional space in which each dimension corresponds to a specific feature or variable used to describe data points. It provides a framework for representing and analyzing the relationships among different data points, enabling various machine learning algorithms to make predictions based on the input features. Understanding feature space is crucial for techniques that transform or manipulate data, such as kernel methods and dimensionality reduction.
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