Length PctPos 1.66 1.62 2.04 1.68 1.62 1.68 2.08 1.82 2.06 1.8 Length 1.66 1.62 2.04...

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Length PctPos 1.66 1.62 2.04 1.68 1.62 1.68 2.08 1.82 2.06 1.8 Length 1.66 1.62 2.04 1.68 1.62 1.68 2.08 1.82 2.06 1.8 0.84 0.86 0.7 0.78 0.76 0.88 0.66 0.66 0.68 0.64 PctPos 0.84 0.86 0.7 0.78 0.76 0.88 0.66 0.66 0.68 0.64 Pct Neg Category 0.28 C 0.25 A 0.23 B 0.03 A 0.95 A 0.02 A 0.29 B 0.58 C 0.53 B 0.41 C Pct Neg Category 0.28 C 0.25 A 0.23 B 0.03 A 0.95 A 0.02 A 0.29 B 0.58 C 0.53 B 0.41 C We observed 10 samples of the products. The column A-C are the attributes of the 10 products, and the column D is the category of the products. Now we have a new product, with the following stats: Length: 1.5 PctPos: 0.5 PctNeg: 0.5 Please use KNN to classify this new prodcut. Please use K = 3 (3 nearest neighbors). KNN Length PctPos 1.66 1.62 2.04 1.68 1.62 1.68 2.08 1.82 2.06 1.8 Length 1.66 1.62 2.04 1.68 1.62 1.68 2.08 1.82 2.06 1.8 0.84 0.86 0.7 0.78 0.76 0.88 0.66 0.66 0.68 0.64 PctPos 0.84 0.86 0.7 0.78 0.76 0.88 0.66 0.66 0.68 0.64 Pct Neg Category 0.28 C 0.25 A 0.23 B 0.03 A 0.95 A 0.02 A 0.29 B 0.58 C 0.53 B 0.41 C Pct Neg Category 0.28 C 0.25 A 0.23 B 0.03 A 0.95 A 0.02 A 0.29 B 0.58 C 0.53 B 0.41 C We observed 10 samples of the products. The column A-C are the attributes of the 10 products, and the column D is the category of the products. Now we have a new product, with the following stats: Length: 1.5 PctPos: 0.5 PctNeg: 0.5 Please use KNN to classify this new prodcut. Please use K = 3 (3 nearest neighbors). KNN