statsmodels-js - MLR 구현

- 참고

https://github.com/egusahiroaki/statsmodels-js

GitHub - egusahiroaki/statsmodels-js: JavaScript Statistical Libraries

 

- code

import React from 'react';
import './App.css';

function App() {
  const Stats = require("statsmodels-js");
  
  //예시 data
  const x = [
    [10, 20, 30],
    [20, 42, 63],
    [4, 8, 16],
  ];
  const y = [30, 50, 70];
  const xTest = [
    [10, 20, 30],
    [1, 2, 3],
  ];
  
  // 모델학습
  const model = new Stats.MultipleLinearRegression(x, y).fit();
  
  // 결과
  let modelSummary = model.summary();
  console.log(modelSummary);

  // 회귀식 출력을 위한 컬럼명 출력
  // let columns = modelSummary.keys();
  // console.log(columns)

  // 회귀식 만들기
  let str_fml = 'y = ';
  for(let prop in modelSummary){
    if (prop == 'intercept'){
      str_fml += `${modelSummary[prop]}`
    }
    else if (prop == 'r2Score'){
      str_fml += ''
    }
    else{
      str_fml += `${Math.round(modelSummary[prop],2)}*${prop} + `
    }
  }
  console.log(str_fml)
  
  // 예측
  let result = model.predict(xTest);
  function makeRound(x){
    return Math.round(x*100 + Number.EPSILON) / 100
  }
  // let result_round = result.map(x => Math.round(x));
  // let result_round = result.map(x => Math.round(x*100 + Number.EPSILON) /100 );
  let result_round = result.map(x => makeRound(x));
  let r2 = modelSummary.r2Score;
  console.log(result_round);

  return (
    <div className="App">
      <header className="App-header">
        <h3>test statsmodels-js</h3>
        <p>pred_y_values: {result_round.join(', ')}</p>
        <p>r2: {r2}</p>
        <p>formula: {str_fml}</p>
      </header>
    </div>
  );
}

export default App;