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    tf-kmeans
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    0.0.3 • Public • Published

    TF-KMeans

    Description

    A Simple JavaScript Library to make it easy for people to use KMeans algorithms with Tensorflow JS.

    The library was born out of another project in which except KMeans, our code completely depended on TF.JS

    As such, moving to TF.JS helped standardise our code base substantially and reduce dependency on other libraries

    Sample Code

        const KMeans = require("tf-kmeans");
        const tf = require("@tensorflow/tfjs");
        const kmeans = new KMeans.default({
            k: 2,
            maxIter: 30,
            distanceFunction: KMeans.default.EuclideanDistance
        });
        const dataset = tf.tensor([[2, 2, 2], [5, 5, 5], [3, 3, 3], [4, 4, 4], [7, 8, 7]]);
        const predictions = kmeans.Train(
            dataset
        );
     
        console.log("Assigned To ", predictions.arraySync());
        console.log("Centroids Used are ", kmeans.Centroids().arraySync());
        console.log("Prediction for Given Value is");
        kmeans.Predict(tf.tensor([2, 3, 2])).print();

    You can use the Asynchronous TrainAsync if you want to use an asynchronous callback function

        const kmeans = new KMeans.default({
            k: 3,
            maxIter: 30,
            distanceFunction: KMeans.default.EuclideanDistance
        });
        const dataset = tf.tensor([[2, 2, 2], [5, 5, 5], [3, 3, 3], [4, 4, 4], [7, 8, 7]]);
     
        console.log("\n\nAsync Test");
        const predictions = await kmeans.TrainAsync(
            dataset,
            // Called At End of Every Iteration
            // This function is Asynchronous
            async(iter, centroid, preds)=>{
                console.log("===");
                console.log("Iteration Count", iter);
                console.log("Centroid ", await centroid.array());
                console.log("Prediction ", await preds.array());
                console.log("===");
                // You could instead use TFVIS for Plotting Here
            }
        );

    Functions

    1. Constructor

      Takes 3 Optional parameters

      1. k:- Number of Clusters
      2. maxIter:- Max Iterations
      3. distanceFunction:- The Distance function Used Currently only Eucledian Distance Provided
    2. Train

      Takes Dataset as Parameter

      Performs Training on This Dataset

      Sync callback function is optional

    3. TrainAsync

      Takes Dataset as Parameter

      Performs Training on This Dataset

      Also takes async callback function called at the end of every iteration

    4. Centroids

      Returns the Centroids found for the dataset on which KMeans was Trained

    5. Predict

      Performs Predictions on the data Provided as Input

    PEER DEPENDENCIES

    1. TensorFlow.JS

    Typings

    As the code is originally written in TypeScript, Type Support is provided out of the box

    Contact Me

    You could contact me via LinkedIn You could file issues or add features via Pull Requests on GitHub

    Install

    npm i tf-kmeans

    DownloadsWeekly Downloads

    7

    Version

    0.0.3

    License

    MIT

    Unpacked Size

    25.3 kB

    Total Files

    9

    Last publish

    Collaborators

    • pratikpc