+**Principal Components** are the new, orthogonal axes that capture the most variance in complex data, transforming it into a simpler, lower-dimensional representation. They reveal the core structure, aiding in [Data Analysis](/wiki/data_analysis) and effectively reducing [Dimensionality](/wiki/dimensionality) by focusing on the most informative directions.
+## See also
+- [Machine Learning](/wiki/machine_learning)
+- [Data Reduction](/wiki/data_reduction)
+- [Factor Analysis](/wiki/factor_analysis)
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