Research Artifacts for Machine Learning DSML Baseball Case Study

Stephan, Matthew; Koseler, Kaan

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This file contains our metamodel, instance models, code generation engine, generated code, and a readme file. The .zip and folder as a whole is (can be opened as) a Papyrus project. (2.188Mb)

The 2016 training data pulled from Baseball Savant. Play-by-play data for pitchers from the Yankees, Reds, Mets, and Blue Jays. (38.07Mb)

The 2017 test data pulled from Baseball Savant. Play-by-play data for pitchers who were on the Yankees, Reds, Mets, and Blue Jays in 2016 (the year prior). (41.51Mb)

The iPython notebook that was used to clean and analyze the 2016/2017 data. (896.9Kb)

Author

Koseler, Kaan

Stephan, Matthew

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Abstract

This entry contains all the artifacts created and data utilized in our research on developing a Machine Learning DSML, models, and software for a Baseball Case Study.

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http://hdl.handle.net/2374.MIA/6234

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Stephan, Matthew

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Except where otherwise noted, this item's license is described as Attribution 3.0 United States (CC BY 3.0 US)

Research Artifacts for Machine Learning DSML Baseball Case Study

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