Principal components refer to a statistical method used to simplify complex data by identifying and focusing on the essential patterns or variables. It involves summarizing a large set of data points into fewer, more manageable components without losing crucial information. These components represent the major sources of variation in the data, making them useful for understanding and analyzing the data more effectively.
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