The k-nearest neighbors algorithm is used for classification of unknown items and involves calculating the distance of the unknown item's neighbors. We'll use Euclidean distance to determine the closest neighbor and make our best guess on what the mystery fruit is.

Just a Euclidean distance, that's all...

function determineFruit({ size, redness }) {
  const fruit = [
    { name: "grape", size: 1, redness: 0 },
    { name: "orange", size: 2, redness: 1 },
    { name: "grapefruit", size: 3, redness: 2 }
  ];

  const { name } = fruit.reduce(
    (prev, cur) => {
      let curCalc = calcDistance([[size, cur.size], [redness, cur.redness]]);
      console.log(curCalc);
      
 
return prev.dist < curCalc ? prev : { name: cur.name, dist: curCalc };
    },
    {
      name: fruit[0].name,
      dist: calcDistance([[size, fruit[0].size], [redness, fruit[0].redness]])
    }
  );
  return `This is most likely a ${name}`;
}

function calcDistance(data) {
  return Math.sqrt(
    data.reduce((acc, curr) 
 
=> console.log(curr) && acc + Math.pow(curr[0] - curr[1], 2), 0)
  );
}

console.log(determineFruit({ size: 2, redness: 2 }));