Ill-conditioned systems refer to mathematical problems or equations where small changes in input can cause large changes in output, making them sensitive to perturbations. This instability can lead to significant inaccuracies in numerical solutions, especially when dealing with data that is noisy or has inherent uncertainties, which is particularly important in data science applications such as regression analysis and machine learning.
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