ml-distance/lib/similarities/kumarHassebrook.js

Distance and similarity functions to compare vectors

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
/**
 *Returns Kumar-Hassebrook similarity between vectors a and b
 * @link [Kumar-Hassebrook Similarity algorithm](https://www.naun.org/main/NAUN/ijmmas/mmmas-49.pdf)
 * @param a - first vector
 * @param b - second vector
 *
 */
function kumarHassebrook(a, b) {
    let p = 0;
    let p2 = 0;
    let q2 = 0;
    for (let i = 0; i < a.length; i++) {
        p += a[i] * b[i];
        p2 += a[i] * a[i];
        q2 += b[i] * b[i];
    }
    return p / (p2 + q2 - p);
}
exports.default = kumarHassebrook;
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