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Native Scoring With SQL Server 2017 R Services

Published 2018-05-29 by Kevin Feasel

Tomaz Kastrun gives us an example using native scoring in SQL Server 2017 Machine Learning Services:

Native scoring in SQL Server 2017 comes with couple of limitations, but also with a lot of benefits. Limitations are:

  • currently supports only SQL server 2017 and Windows platform

  • trained model should not exceed 100 MiB in size

  • Native scoring with PREDICT function supports only following algorithms from RevoScaleR library:

    • rxLinMod (linear model as linear regression)

    • rxLogit (logistic regression)

    • rxBTrees (Parallel external memory algorithm for Stochastic Gradient Boosted Decision Trees)

    • rxDtree (External memory algorithm for Classification and Regression Trees

    • rxDForest (External memory algorithm for Classification and Regression Decision Trees)

Read on for an example.  If you’re using one of these methods, then native scoring is extremely fast and a bit more flexible than I originally anticipated.  The problem is that you have to use one of those methods.

Published in R