Two of the trickiest qualities to stability on the earth of machine studying are equity and accuracy. Algorithms optimized for accuracy could unintentionally perpetuate bias towards particular teams, whereas these prioritizing equity could compromise accuracy by misclassifying some knowledge factors.
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