diff --git a/.gitignore b/.gitignore deleted file mode 100644 index 40b878d..0000000 --- a/.gitignore +++ /dev/null @@ -1 +0,0 @@ -node_modules/ \ No newline at end of file diff --git a/README.md b/README.md deleted file mode 100644 index d1b6cfb..0000000 --- a/README.md +++ /dev/null @@ -1,77 +0,0 @@ -# JavaScript Linear Regression - -Ini adalah percobaan implementasi model regresi linear pada program komputer. Program dibuat dengan bahasa pemrograman JavaScript dan dengan *runtime* [Node.js](https://nodejs.org/) dengan tanpa menggunakan bantuan library atau framework pembantu perhitungan matematis. Program yang dibuat ada dua versi, CLI (*Command Line Interface*) dan juga website. - -
- -
- - -# Menjalankan program 🛩ī¸ - -1. Install dependensi yang dibutuhkan - - Pastikan perangkat anda sudah terinstall [Node.js](https://nodejs.org/). Jika sudah, maka lakukan perintah berikut pada terminal perangkat anda: - ```shell - npm install - ``` - -2. Jalankan program di terminal - - Gunakan perintah berikut: - ```shell - npm run cli - ``` - -# Preview program 🤖 - -Berikut adalah contoh ketika program dijalankan: - - - - - - - - - - - - - - -
CLI
- -
Web
- -
- - - -# Kustomisasi 🛠ī¸ - -Anda bisa melakukan kustomisasi pada proyek ini. Kustomisasi bisa dilakukan pada data yang digunakan ataupun alur kerja program. Jika anda ingin melakukan kustomisasi data, maka anda bisa ubah file `.csv` pada folder [`data/`](data/). - -# Kontribusi đŸĢąđŸģ‍đŸĢ˛đŸģ - -Anda bisa melakukan kontribusi pada proyek ini dengan melakukan *fork* pada repositori ini dan unggah perubahan yang anda lakukan ke GitHub. Kemudian Anda bisa mengajukan *pull request* ke repositori ini. Untuk petunjuk lebih lanjut, anda bisa membaca dokumentasi dari GitHub berikut: https://docs.github.com/en/get-started/exploring-projects-on-github/contributing-to-a-project - -Anda juga bisa mengajukan kritik atau saran dengan membuka [*issue*]() di repositori ini. - -# Penutup 🍃 - -Demikian proyek sederhana yang dibuat dengan tujuan melakukan demonstrasi regresi linear menggunakan bahasa pemrograman JavaScript dan *runtime* Node.js. Proyek ini juga bisa menjadi acuan dalam pembelajaran terkait model-model *machine learning* yang lebih kompleks. - -Akhir kata, terima kasih 🙏đŸģ - -# Referensi 📃 - -- [**"The Elements of Statistical Learning"** by Trevor Hastie, Robert Tibshirani, and Jerome Friedman](https://www.sas.upenn.edu/~fdiebold/NoHesitations/BookAdvanced.pdf) -- [**"Mathematics for Machine Learning" by Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong**](https://mml-book.github.io/) - -# Lihat juga 👁ī¸ - -- [**Linear Regression, Clearly Explained**: Youtube video by StatQuest with Josh Starmer](https://youtu.be/nk2CQITm_eo?si=CyoCEtAnBETJYT3E) - ---- ---- \ No newline at end of file diff --git a/src/web/assets/icon/king-js.ico b/assets/icon/king-js.ico similarity index 100% rename from src/web/assets/icon/king-js.ico rename to assets/icon/king-js.ico diff --git a/src/web/assets/icon/king-js.svg b/assets/icon/king-js.svg similarity index 100% rename from src/web/assets/icon/king-js.svg rename to assets/icon/king-js.svg diff --git a/data/goals_shot_on_target.csv b/data/goals_shot_on_target.csv deleted file mode 100644 index bc0d4b3..0000000 --- a/data/goals_shot_on_target.csv +++ /dev/null @@ -1,21 +0,0 @@ -Pos,Club,Played,Goals,Shot On Target -1,Liverpool,19,47,131 -2,Arsenal,20,39,102 -3,Nottingham Forest,20,29,93 -4,Chelsea,20,39,119 -5,Newcastle United,20,34,90 -6,Manchester City,20,30,118 -7,Bournemoth,20,30,114 -8,Aston Villa,20,30,85 -9,Fullham,20,30,98 -10,Brighton and Hove Albion,20,30,94 -11,Brentford,20,38,99 -12,Tottenham Hotspur,20,42,113 -13,Manchester United,20,23,94 -14,West Ham United,20,24,84 -15,Crystal Palace,20,21,101 -16,Everton,19,15,63 -17,Wolverhampton Wanderers,20,31,85 -18,Ipswich Town,20,20,65 -19,Leicester City,20,23,63 -20,Southampton,20,12,58 \ No newline at end of file diff --git a/data/salary_data.csv b/data/salary_data.csv deleted file mode 100644 index 3bf81ad..0000000 --- a/data/salary_data.csv +++ /dev/null @@ -1,21 +0,0 @@ -YearsExperience,Salary -1.1,39343.00 -1.3,46205.00 -1.5,37731.00 -2.0,43525.00 -2.2,39891.00 -2.9,56642.00 -3.0,60150.00 -3.2,54445.00 -3.2,64445.00 -3.7,57189.00 -3.9,63218.00 -4.0,55794.00 -4.0,56957.00 -4.1,57081.00 -4.5,61111.00 -4.9,67938.00 -5.1,66029.00 -5.3,83088.00 -5.9,81363.00 -6.0,93940.00 diff --git a/data/student_performance.csv b/data/student_performance.csv deleted file mode 100644 index 3e20c1b..0000000 --- a/data/student_performance.csv +++ /dev/null @@ -1,21 +0,0 @@ -Hours Studied,Previous Scores,Extracurricular Activities,Sleep Hours,Sample Question Papers Practiced,Performance Index -7,99,Yes,9,1,91.0 -4,82,No,4,2,65.0 -8,51,Yes,7,2,45.0 -5,52,Yes,5,2,36.0 -7,75,No,8,5,66.0 -3,78,No,9,6,61.0 -7,73,Yes,5,6,63.0 -8,45,Yes,4,6,42.0 -5,77,No,8,2,61.0 -4,89,No,4,0,69.0 -8,91,No,4,5,84.0 -8,79,No,6,2,73.0 -3,47,No,9,2,27.0 -6,47,No,4,2,33.0 -5,79,No,7,8,68.0 -2,72,No,4,3,43.0 -8,73,Yes,8,4,67.0 -6,83,Yes,7,2,70.0 -2,54,Yes,4,9,30.0 -5,75,No,7,0,63.0 diff --git a/data/study_hours_vs_test_score.csv b/data/study_hours_vs_test_score.csv deleted file mode 100644 index 4027e9c..0000000 --- a/data/study_hours_vs_test_score.csv +++ /dev/null @@ -1,11 +0,0 @@ -Hours_Studied,Test_Score -1,50 -2,55 -3,60 -4,65 -5,70 -6,75 -7,80 -8,85 -9,90 -10,95 diff --git a/docs/img/cli-program-preview.gif b/docs/img/cli-program-preview.gif deleted file mode 100644 index 8660400..0000000 Binary files a/docs/img/cli-program-preview.gif and /dev/null differ diff --git a/docs/img/king-js.svg b/docs/img/king-js.svg deleted file mode 100644 index 433b7b4..0000000 --- a/docs/img/king-js.svg +++ /dev/null @@ -1,6 +0,0 @@ - - - - - - diff --git a/docs/img/linear-graph-gif.gif b/docs/img/linear-graph-gif.gif deleted file mode 100644 index 75796da..0000000 Binary files a/docs/img/linear-graph-gif.gif and /dev/null differ diff --git a/docs/img/web-program-preview.gif b/docs/img/web-program-preview.gif deleted file mode 100644 index 6381d8f..0000000 Binary files a/docs/img/web-program-preview.gif and /dev/null differ diff --git a/eslint.config.js b/eslint.config.js deleted file mode 100644 index 6d1eeba..0000000 --- a/eslint.config.js +++ /dev/null @@ -1,9 +0,0 @@ -import globals from "globals"; -import pluginJs from "@eslint/js"; - - -/** @type {import('eslint').Linter.Config[]} */ -export default [ - {languageOptions: { globals: globals.browser }}, - pluginJs.configs.recommended, -]; \ No newline at end of file diff --git a/src/web/index.html b/index.html similarity index 100% rename from src/web/index.html rename to index.html diff --git a/package-lock.json b/package-lock.json deleted file mode 100644 index 2895097..0000000 --- a/package-lock.json +++ /dev/null @@ -1,1631 +0,0 @@ -{ - 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Program dibuat dengan bahasa pemrograman JavaScript dan dengan *runtime* [Node.js](https://nodejs.org/). Program ini sepenuhnya berjalan di terminal dan dengan bantuan aplikasi Geogebra sebagai bantuan visualisasi data.", - "main": "index.js", - "directories": { - "doc": "docs" - }, - "type": "module", - "dependencies": { - "chalk": "^5.4.1", - "cli-table3": "^0.6.5", - "csv-parser": "^3.1.0", - "inquirer": "^12.3.2" - }, - "devDependencies": { - "@eslint/js": "^9.18.0", - "eslint": "^9.18.0", - "globals": "^15.14.0" - }, - "scripts": { - "test": "echo \"Error: no test specified\" && exit 1", - "cli": "node src/cli/main.js" - }, - "repository": { - "type": "git", - "url": "git+https://github.com/FarrelAD/JavaScript-Linear-Regression-Model.git" - }, - "keywords": [], - "author": "", - "license": "ISC", - "bugs": { - "url": "https://github.com/FarrelAD/JavaScript-Linear-Regression-Model/issues" - }, - "homepage": "https://github.com/FarrelAD/JavaScript-Linear-Regression-Model#readme" -} diff --git a/src/web/script.js b/script.js similarity index 100% rename from src/web/script.js rename to script.js diff --git a/src/cli/main.js b/src/cli/main.js deleted file mode 100644 index 69a14ff..0000000 --- a/src/cli/main.js +++ /dev/null @@ -1,163 +0,0 @@ -import fs from 'fs' -import { readdir } from 'fs/promises' -import path from 'path' -import { fileURLToPath } from 'url' -import { exit } from 'process' -import chalk from 'chalk' -import { confirm, select } from '@inquirer/prompts' -import csv from 'csv-parser' -import Table from 'cli-table3' - -import singleFeatureProcess from './single-feature.js' -import multiFeatureProcess from './multi-feature.js' - - - - -// Simplify std out from `console.log` into `print` -const print = console.log; - - -const DATA_DIR = path.join(path.dirname(fileURLToPath(import.meta.url)), '..', '..', 'data'); - - -///////////////////////////////////////////////////////////////////// -//// 6MMMMb\ MMMMMMMMMM dM. `MMMMMMMb. MMMMMMMMMM ///// -//// 6M' ` / MM \ ,MMb MM `Mb / MM \ ///// -//// MM MM d'YM. MM MM MM ///// -//// YM. MM ,P `Mb MM MM MM ///// -//// YMMMMb MM d' YM. MM .M9 MM ///// -//// `Mb MM ,P `Mb MMMMMMM9' MM ///// -//// MM MM d' YM. MM \M\ MM ///// -//// MM MM ,MMMMMMMMb MM \M\ MM ///// -//// L ,M9 MM d' YM. MM \M\ MM ///// -//// MYMMMM9 _MM_ _dM_ _dMM__MM_ \M\_ _MM_ ///// -///////////////////////////////////////////////////////////////////// - -do { - console.clear() - print( -`========================== - WELCOME! -========================== -SIMPLE LINEAR REGRESSION DEMO -`) - - const answers = await select({ - message: 'Choose menu', - choices: [ - '1. Guide', - '2. Run Demo', - '3. Exit' - ] - }) - - console.clear() - - - switch (answers) { - case '1. Guide': await showGuide(); break; - case '2. Run Demo': await runDemo(); break; - case '3. Exit': print('Thanks, bye!'); exit(0); - } -} while (await confirm({ message: 'Continue program?' })) - - - - - - -async function showGuide() { - print('This is a guide for this program!'); - for (let i = 1; i <= 5; i++) { - print('Data: ', i) - } - - - if (!await confirm({ message: 'Back?'})) { - exit(0) - } -} - - - -async function runDemo() { - let files - try { - print('Scanning data input file ...') - files = await readdir(DATA_DIR) - } catch (error) { - print(chalk.red('Error reading directory: ', error.message)) - return; - } - - - const answers = await select({ - message: 'Choose data', - choices: files - }) - - if (await confirm({ message: 'Preview data?'})) { - await previewData(answers) - } -} - - - -function readFileAsync(filePath) { - return new Promise((resolve, reject) => { - const data = [] - fs.createReadStream(filePath) - .pipe(csv()) - .on('data', (row) => data.push(row)) - .on('end', () => resolve(data)) - .on('error', (error) => reject(error)) - }) -} - - - -async function previewData(filePath) { - print('\n-----------------------------------------------------\n') - print('Preview data: ', filePath) - - const data = await readFileAsync(path.join(DATA_DIR, filePath)) - - const table = new Table({ - head: Object.keys(data[0]) - }) - - data.forEach(row => { - table.push(Object.values(row)) - }) - - print(table.toString()) - - if (await confirm({ message: 'Continue next process' })) { - await dataIdentification(data) - } -} - - - -async function dataIdentification(data) { - console.clear() - print('-----------------------------------------------------\n') - print('Data identification') - - - const answers = await select({ - message: 'Choose model type', - choices: [ - '1. Single feature', - '2. Multi feature' - ] - }) - - console.clear() - - switch (answers) { - case '1. Single feature': await singleFeatureProcess(data); break; - case '2. Multi feature': await multiFeatureProcess(data); break; - } -} diff --git a/src/cli/multi-feature.js b/src/cli/multi-feature.js deleted file mode 100644 index 0159aa2..0000000 --- a/src/cli/multi-feature.js +++ /dev/null @@ -1,147 +0,0 @@ -import process from 'process' -import chalk from 'chalk' -import inquirer from 'inquirer' -import { confirm } from '@inquirer/prompts' - - - -// Simplify std out from `console.log` into `print` -const print = console.log; - - - -/** - * Process linear regression with multi feature - * - * Formula - * y = a + bx - * - * @param {Array} data - the raw data - */ -export default async function multiFeatureProcess(data) { - print('=====================================================\n') - print(chalk.blue('MULTI FEATURE PROCESS\n')) - - const answers = await inquirer.prompt([ - { - type: 'checkbox', - name: 'features', - message: 'Choose independent variable', - choices: Object.keys(data[0]) - }, - { - type: 'list', - name: 'label', - message: 'Choose dependent variable', - choices: Object.keys(data[0]) - } - ]) - - - for (const feature of answers.features) { - if (feature == answers.label) { - print(chalk.redBright('\n[!] Feature and label can not be same')) - - if (await confirm({ message: 'Back?'})) return; - } - } - - - /** - * Raw data validation. Make sure all feature and label are number - */ - const numberPattern = /^[+-]?\d+(\.\d+)?$/ - for (const item of data) { - if (!numberPattern.test(item[answers.label])) { - print(chalk.redBright('\n[!] Some data is not a number! Unable to process further!')) - await confirm({ message: 'Continue?'}) - return; - } - - for (const feature of answers.features) { - if (!numberPattern.test(item[feature])) { - print(chalk.redBright('\n[!] Some data is not a number! Unable to process further!')) - await confirm({ message: 'Continue?'}) - return; - } - } - } - - - /** - * Calculate the value a and b to get equation y = a + bx - */ - const sumY = data.reduce((sum, val) => sum + parseInt(val[answers.label]), 0) - - const sumXi = [] - const sumXiSquared = [] - const sumXiYi = [] // ? how ? - - for (let i = 0; i < answers.features.length; i++) { - sumXi.push(data.reduce((sum, val) => sum + parseInt(val[answers.features[i]]), 0)) - sumXiSquared.push(data.reduce((sum, val) => sum + parseInt(val[answers.features[i]]) ** 2, 0)) - } - - const sumAllXi = sumXi.reduce((sum, val) => sum * val) - const sumAllXiSquared = sumXiSquared.reduce((sum, val) => sum * val) - - const slopes = [] - for (let i = 0; i < answers.features.length; i++) { - slopes.push( - ((data.length * sumXiYi) - (sumAllXi * sumY)) / - ((data.length * sumAllXiSquared) - (sumAllXi ** 2)) - ) - } - - let sumSlopeiXi = 0 - for (let i = 0; i < slopes.length; i++) { - sumSlopeiXi += slopes[i] * (sumXi[i] / data.length) - } - - - /** - * INSPECTION! - */ - // print('sumY: ', sumY) - // print('sumXi: ', sumXi) - // print('slopes: ', slopes) - // print('sumXiSquare: ', sumXiSquared) - // print('sumAllXiSquared: ', sumAllXiSquared) - // print('sumXiYi: ', sumXiYi) - - const a = (sumY / data.length) - sumSlopeiXi - - // Equation result - const y = (x) => a + slopes.reduce((sum, val, index) => sum + (val * x[index])) - - - // Print the equation - process.stdout.write(chalk.blueBright(`\nEquation result: ${a} + `)) - - slopes.forEach((val, index) => { - process.stdout.write(chalk.blueBright(`${val}x\u1d62`)) - if (index != slopes.length - 1) process.stdout.write(chalk.blueBright(' + ')) - }) - - print('\n\r') - - if (await confirm({ message: 'Do you want to test?'})) { - do { - await testing(y, answers.features, answers.label) - } while (await confirm({ message: 'Do you want to test again?'})); - } -} - - -async function testing(y, features, label) { - const inputInquirer = features.map(feature => { - return { - type: 'number', - name: feature, - message: `Input ${feature}` - } - }) - - const inputFeatures = await inquirer.prompt(inputInquirer) - print(`Prediction ${label}:`, chalk.blueBright(`${y(Object.values(inputFeatures))}`)) -} diff --git a/src/cli/single-feature.js b/src/cli/single-feature.js deleted file mode 100644 index 482e79b..0000000 --- a/src/cli/single-feature.js +++ /dev/null @@ -1,114 +0,0 @@ -import chalk from 'chalk' -import inquirer from 'inquirer' -import { input, confirm } from '@inquirer/prompts' - - - -/** - * Simplify std out from `console.log` into `print` - */ -const print = console.log; - - - -/** - * Process linear regression with single feature - * - * Formula - * `y = β0 ​+ β1​x1` - * - * @param {Array} data - the raw data - */ -export default async function singleFeatureProcess(data) { - print('=====================================================\n') - print(chalk.blue('SINGLE FEATURE PROCESS\n')) - - const answers = await inquirer.prompt([ - { - type: 'list', - name: 'feature', - message: 'Choose feature', - choices: Object.keys(data[0]) - }, - { - type: 'list', - name: 'label', - message: 'Choose label', - choices: Object.keys(data[0]) - } - ]) - - if (answers.feature == answers.label) { - print(chalk.redBright('\n[!] Feature and label can not be same')) - - await confirm({ message: 'Back?'}) - return - } - - - const numberPattern = /^[+-]?\d+(\.\d+)?$/ - for (const item of data) { - if (!numberPattern.test(item[answers.feature]) || !numberPattern.test(item[answers.label])) { - print(chalk.redBright('\n[!] Some data is not a number! Unable to process further!')) - await confirm({ message: 'Continue?'}) - return - } - } - - - const equation = modelling(data, answers) - - - if (await confirm({ message: 'Do you want to test?'})) { - do { - await testing(equation, answers.feature, answers.label) - } while (await confirm({ message: 'Do you want to test again?'})); - } -} - - - -/** - * Calculate the value a and b to get equation y = a + bx - * a : intercept - * b : slope - * - * `feature` is `x` and `label` is `y` - * - * @param {Array} data - raw data - * @param {Object} answers - the input of features and label from user - * @returns {function(x): number} a function of linear equation - */ -function modelling(data, answers) { - const sumX = data.reduce((sum, val) => sum + parseFloat(val[answers.feature]), 0) - const sumY = data.reduce((sum, val) => sum + parseFloat(val[answers.label]), 0) - const sumXY = data.reduce((sum, val) => sum + (parseFloat(val[answers.feature]) * parseFloat(val[answers.label])), 0) - const sumXSquared = data.reduce((sum, val) => sum + parseFloat(val[answers.feature]) ** 2, 0) - const sumXTimesSumY = sumX * sumY - - const b = ( - ((data.length * sumXY) - sumXTimesSumY) / - ((data.length * sumXSquared) - (sumX ** 2)) - ) - - const a = (sumY / data.length) - (b * (sumX / data.length)) - - /** - * Linear equation result based on data processing - * - * @param {number} x - a feature data - * @returns {number} a label/target/`y` value result - */ - const y = (x) => a + (b * x) - - // Print the equation - print(chalk.blueBright(`\nEquation result: y = ${a} + ${b}x`)) - - return y -} - - -async function testing(equation, feature, label) { - const inputFeature = await input({message: `Input ${feature}`}) - print(`Prediction ${label}: ${equation(inputFeature)}`) -} diff --git a/src/web/tailwind.config.js b/tailwind.config.js similarity index 100% rename from src/web/tailwind.config.js rename to tailwind.config.js