English to Russian Tech/Engineering IT (Information Technology) Machine learning

So whenever you're building a prediction model the goal is to reduce this overall quantity. So this is basically the expected. Mean squared error between our our outcome and our prediction. And so, the irreducible error can't usually be reduced. It's value that's just part of the data you're collecting. But you can *trade off bias and variance*. And that's what the idea behind regularized regression does.
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