Digital Twin Analytics SEARCH: Generating initial ML Results for an Unidentified Dataset

This package utilizes different components of SEARCH: store, explore, assess, reduce, confirm, and holistic to generate initial machine learning results for an unidentified data set.
Technology No. CW-23-38

The purpose of this software is to generate initial machine learning results for an unidentified data set. This package leverages various components of SEARCH: store, explore, assess, reduce, confirm, and holistic. It allows for analysis of a given data set by preprocessing the data, selecting suitable algorithms for analysis, performing dimension reduction, validating results through multiple imputations of the data, and providing user-friendly documentation. It has diverse applications in machine learning and serves as an open-source, edge-based automated machine learning platform.

  • swap_vertical_circlemode_editAuthors (5)
    Matthew Kunz
    Katherine Wilsdon
    Shaw Wen
    Thomas Conley
    Dawn Galloway
  • swap_vertical_circlecloud_downloadSupporting documents (1)
    Product brochure
    Digital Twin Analytics SEARCH: Generating initial ML Results for an Unidentified Dataset.pdf
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