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.+One+key+result+of+our+work+is+that+stratification+via+k-means+clustering+based+on+accurate+predictions+of+model+performance+yields+efficient+estimators.+Our+experiments+on+computer+vision+datasets+show+that+this+method+consistently+provides+more+precise+accuracy+estimates+than+the+traditional+simple+random+sampling%252C+even+with+substantial+efficiency+gains+of+10x.+We+also+find+that+model-assisted+estimators%252C+which+leverage+predictions+of+model+accuracy+on+the+unlabeled+portion+of+the+dataset%252C+are+generally+more+efficient+than+the+traditional+estimates+based+solely+on+the+labeled+data.&cdnurl=https%3a%2f%2fth.bing.com%2fth%2fid%2fR.1a62df4dd87618a3aa1d76859d81ae32%3frik%3dlz7C6LpSZILjlQ%26pid%3dImgRaw%26r%3d0&exph=630&expw=1200&q=Why+Do+We+Need+Model+Evaluation&FORM=IRPRST&ck=772F07790C266CFB0FF22FFF779080F1&selectedIndex=33&itb=0)
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