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For those of us not well-versed in decision trees, could you provide an explanation of bias and variance and how they're pertinent? Additionally, could you share with us which of those two is tougher to deal with: high bias or high variance - and why?

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Interview question asked to Data Scientists interviewing at DoorDash, Curve, Thumbtack and others: For those of us not well-versed in decision trees, could you provide an explanation of bias and variance and how they're pertinent? Additionally, could you share with us which of those two is tougher to deal with: high bias or high variance - and why?.