K-nearest neighbors
JavaScript, Algorithm, Array · Oct 13, 2021
Classifies a data point relative to a labelled data set, using the k-nearest neighbors algorithm.
- Use
Array.prototype.map()to map thedatato objects. Each object contains the euclidean distance of the element frompoint, calculated usingMath.hypot(),Object.keys()and itslabel. - Use
Array.prototype.sort()andArray.prototype.slice()to get theknearest neighbors ofpoint. - Use
Array.prototype.reduce()in combination withObject.keys()andArray.prototype.indexOf()to find the most frequentlabelamong them.
const kNearestNeighbors = (data, labels, point, k = 3) => {
const kNearest = data
.map((el, i) => ({
dist: Math.hypot(...Object.keys(el).map(key => point[key] - el[key])),
label: labels[i]
}))
.sort((a, b) => a.dist - b.dist)
.slice(0, k);
return kNearest.reduce(
(acc, { label }, i) => {
acc.classCounts[label] =
Object.keys(acc.classCounts).indexOf(label) !== -1
? acc.classCounts[label] + 1
: 1;
if (acc.classCounts[label] > acc.topClassCount) {
acc.topClassCount = acc.classCounts[label];
acc.topClass = label;
}
return acc;
},
{
classCounts: {},
topClass: kNearest[0].label,
topClassCount: 0
}
).topClass;
};const data = [[0, 0], [0, 1], [1, 3], [2, 0]];
const labels = [0, 1, 1, 0];
kNearestNeighbors(data, labels, [1, 2], 2); // 1
kNearestNeighbors(data, labels, [1, 0], 2); // 0
