Berkson's Paradox in Machine Learning
<p>Sometimes, statistics show surprising things that make us question what we see daily. Berkson's Paradox is one example of this. This Paradox is strongly related to the sampling bias problem and occurs when we mistakenly think that two things are related because we don't see the whole picture. As a machine learning expert, you should be familiar with this Paradox because it can significantly impact the accuracy of your predictive models by leading to incorrect assumptions about the relationship between variables.</p>
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