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    A Summary of Using k-NN in Production

    on October 8, 2016

    This week, Domino’s Chief Data Scientist, Eduardo Ariño de la Rubia, presented a webinar: An Introduction to Using k-NN in Production. If you missed the live webinar or would like to watch it again, you can find a recording below:

    http://dominodatalab.wistia.com/medias/jggs1iy570?embedType=async videoFoam=true videoWidth=640

    k-Nearest Neighbors is a simple algorithm that stores all available cases and classifies new cases based on a similarity measure (e.g., distance functions). Watch the webinar to learn:

    • Different implementations of using k-NN in production;
    • The pros and cons of using the algorithm with production data sets;
    • How to use R and Python packages to get the most out of your k-NN model;
    • A demonstration of training models on the Domino platform.

    If you’d like to benchmark the predictive performance of k-NN against other algorithms contact us for a personalized demo of the Domino data science platform.

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