@ryanuo/utils/dist/lib/ai/machine.cjs

提供多种实用工具函数，涵盖算法、浏览器操作、网络请求等多个领域

"use strict";

Object.defineProperty(exports, "__esModule", {
  value: true
});
exports.linearRegression = linearRegression;
exports.normalizeData = normalizeData;
exports.normalizeMinMax = normalizeMinMax;
function normalizeData(data, mean, stdDev) {
  if (stdDev === 0) throw new Error("division by zero");
  return data.map(value => (value - mean) / stdDev);
}
function normalizeMinMax(data) {
  const min = Math.min(...data);
  const max = Math.max(...data);
  if (min === max) return data.map(() => 0);
  return data.map(value => (value - min) / (max - min));
}
function linearRegression(data) {
  if (data.length === 1) {
    return data[0];
  }
  const n = data.length;
  const x = Array.from({
    length: n
  }, (_, i) => i);
  const y = data;
  const xMean = x.reduce((sum, val) => sum + val, 0) / n;
  const yMean = y.reduce((sum, val) => sum + val, 0) / n;
  const numerator = x.reduce((sum, xi, idx) => sum + (xi - xMean) * (y[idx] - yMean), 0);
  const denominator = x.reduce((sum, xi) => sum + (xi - xMean) ** 2, 0);
  const m = numerator / denominator;
  const b = yMean - m * xMean;
  const nextX = n;
  return m * nextX + b;
}