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ml_uncertainty: A Python module for estimating uncertainty in predictions of machine learning models
Data provided by National Institute of Standards and Technology
This software is a Python module for estimating uncertainty in predictions of machine learning models. It is a Python package that calculates uncertainties in machine learning models using bootstrapping and residual bootstrapping. It is intended to interface with scikit-learn but any Python package that uses a similar interface should work.
Tags: uncertainty analysis,machine learning,model calibration,
Modified: 2024-02-22
Views: 0
Nestor: a toolkit for quantifying tacit maintenance knowledge, for investigatory analysis in smart manufacturing
Data provided by National Institute of Standards and Technology
There is often a large amount of maintenance data already available for use in Smart Manufacturing systems, but in a currently-unusable form: service tickets and maintenance work orders (MWOs). Nestor is a toolkit for using Natural Language Processing (NLP) with efficient user-interaction to perform structured data extraction with minimal annotation time-cost.
Tags: information,communication,maintenance,tribal knowledge,event sequences,training,machine learning,data cleaning,prognostics,diagnostics,visualization,decision guidance,CMMS,scheduling,investigations,nestor,smart manufacturing,manufacturing operations,manufacturing performance,
Modified: 2024-02-22
Views: 0