ydf-training

YDF Training in JS

With this package, you can train machine learning models with YDF in the browser and with Node.js.

Usage example

This package supports multiple surfaces.

Run the model with in Browser

<script src="./node_modules/ydf-training/dist/training.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jszip/3.10.0/jszip.min.js"></script>
<script>
YDFTraining()
    .then(ydf => fetch("http://localhost:3000/data.csv"))
    .then( async (response) => {
      const data = await response.text()
      const task = "CLASSIFICATION";
      const label = "label";
      const model = new ydf.GradientBoostedTreesLearner(label, task).train(data);
      const predictions = model.predict(data);
      console.log(model.describe());
      const modelAsZipBlob = await model.save();
      model.unload();
    });
</script>

Run the model with NodeJS and CommonJS

(async function (){
    // Load the YDF library.
    const ydf = await require("ydf-training")();

    // Load the model.
    const fs = require("node:fs");
    const data = fs.readFileSync("data.csv", 'utf-8');
    const task = "CLASSIFICATION";
    const label = "label";
    const model = new ydf.GradientBoostedTreesLearner(label, task).train(data);

    // Make predictions.
    const predictions = model.predict(data);
    console.log("predictions:", predictions);

    // Describe the model.
    const description = model.describe();
    console.log( predictions);

    // Save the model to disk.
    var fileReader = new FileReader();
    fileReader.onload = function() {
      fs.writeFileSync('model.zip', Buffer.from(new Uint8Array(this.result)));
    };
    const blob = await model.save();
    fileReader.readAsArrayBuffer(blob);

    // Release model
    model.unload();
}())

Run the model with NodeJS and ES6

import * as fs from "node:fs";
import YDFTraining from 'ydf-training';

// Load the YDF library
let ydf = await YDFTraining();

const data = fs.readFileSync("data.csv", 'utf-8');
const task = "CLASSIFICATION";
const label = "label";
const model = new ydf.GradientBoostedTreesLearner(label, task).train(data);

// Make predictions.
const predictions = model.predict(data);
console.log("predictions:", predictions);

// Describe the model.
const description = model.describe();
console.log( predictions);

// Save the model to disk.
var fileReader = new FileReader();
fileReader.onload = function() {
  fs.writeFileSync('model.zip', Buffer.from(new Uint8Array(this.result)));
};
const blob = await model.save();
fileReader.readAsArrayBuffer(blob);

// Release model
model.unload();

For developers

Run unit tests

npm test

Update the binary bundle

Building the binary bundle requires Bazel and Node.js installed.

# Assume the shell is located in a clone of:
# https://github.com/google/yggdrasil-decision-forests.git

# Compile the YDF Training
yggdrasil_decision_forests/port/javascript/tools/build_zipped_library.sh

You can find the compiled bundle in third_party/yggdrasil_decision_forests/port/javascript/training/npm/