Javascript

YDF offers two different npm packages to run on the web:

• ydf-inference Only for generating predictions using an existing model. Models can be trained with ydf-training (see below), YDF python, or any other YDF API. If you only need model predictions, use this package instead of ydf-training to save on binary size.
• ydf-training for both training models and generating predictions.

Both packages are compatible with NodeJS+CommonJS, NodeJS+ES6 and Browser JS.

ydf-inference

ydf-inference is YDF's interface for model inference on the Web. See the Readme on npmjs.com for information about downloading and testing the package.

The following example shows how to download a YDF model and make predictions on a Javascript dictionary of arrays.

<script src="./node_modules/ydf-inference/dist/inference.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/jszip/3.10.0/jszip.min.js"></script>
<script>
YDFInference()
    .then(ydf => ydf.loadModelFromUrl("http://localhost:3000/model.zip"))
    .then(model => {
        let examples = {
            "age": [39, 40, 40, 35],
            "workclass": ["State-gov", "Private", "Private", "Federal-gov"],
            "fnlwgt": [77516, 121772, 193524, 76845],
            "education": ["Bachelors", "Assoc-voc", "Doctorate", "9th"],
            "education_num": ["13", "11", "16", "5"],
            "marital_status": ["Never-married", "Married-civ-spouse", "Married-civ-spouse", "Married-civ-spouse"],
            "occupation": ["Adm-clerical", "Craft-repair", "Prof-specialty", "Farming-fishing"],
            "relationship": ["Not-in-family", "Husband", "Husband", "Husband"],
            "race": ["White", "Asian-Pac-Islander", "White", "Black"],
            "sex": ["Male", "Male", "Male", "Male"],
            "capital_gain": [2174, 0, 0, 0],
            "capital_loss": [0, 0, 0, 0],
            "hours_per_week": [40, 40, 60, 40],
            "native_country": ["United-States", null, "United-States", "United-States"]
        };
        predictions = model.predict(examples);
        model.unload();
    });
</script>

ydf-training

ydf-training is YDF's interface for training and inspecting models in Javascript. It is implemented with Javascript and WebAssembly. See the Readme on npmjs.com for information about downloading and testing the package.

The following example shows how to train a Gradient Boosted Trees model on a first csv dataset, and then use this model to make predictions on a second csv dataset.

<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( async (ydf) => {
      // Download the datasets.
      const rawTrain = await fetch("http://localhost:3000/train.csv");
      const train = await rawTrain.text();
      const rawTest = await fetch("http://localhost:3000/test.csv");
      const test = await rawTest.text();

      // Prepare the training configuration.
      const task = "CLASSIFICATION";
      const label = "label";

      // Train the model.
      const model = new ydf.GradientBoostedTreesLearner(label, task).train(data);

      // Make predictions.
      const predictions = model.predict(data);

      // Print the description of the model.
      console.log(model.describe());

      // Save the model to later. This model can also be run with ydf-inference
      // or Python YDF.
      const modelAsZipBlob = await model.save();
      model.unload();
    });
</script>

Known limitations

ydf-training currently only supports a subset of the functionality of YDF's Python surface, namely supervised learning with Random Forests and Gradient Boosted Trees. Hyperparameter configuration is not yet supported. Additionally, model evaluation and model analysis are not yet supported.

For feature requests, please open an issue on GitHub.