A Summary of Using k-NN in Production

by on October 7, 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:

 

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, , download our Benchmarking Predictive Models Guide. Or contact us for a personalized demo of the Domino data science platform.

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