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

INL Software; Matthew Kunz; Katherine Wilsdon; Shaw Wen; Thomas Conley; Dawn Galloway

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

INL Software (Photographer), Matthew Kunz (Developer), Katherine Wilsdon (Developer), Shaw Wen (Developer), Thomas Conley (Developer), Dawn Galloway (Developer)

Systems Science & Engineering

Research output: Non-textual form › Software

Abstract

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.

Original language	American English
State	Published - 2024

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https://inlsoftware.inl.gov/product/digitaltwinanalytics

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abstract = "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.",

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

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