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Table of Contents1. Background 2. Overview of Classification and Coding 3. Data pre-processing 4. Algorithms 5. Quality measure used in Classification and Coding 6. Classification and Coding Pilot Studies 7. Value added by Classification and Coding using ML in the production of official statistics 8. Expected value added not shown 9. Best practises 10. Comparison of results 11. Conclusions |
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The UNECE Machine Learning project was recommended by the HLG-MOS – Blue Sky Thinking network in the autumn of 2018, approved early 2019 and launched in March 2019. The objective of the project is to advance the research, development and application of Machine Learning (ML) techniques to add value to the production of official statistics.
Three themes were investigated:
This report attempts to summarise and investigates how and if the pilot studies carried out on Classification and Coding have shown to make official statistics better, where better can be any one or more aspects of:
Advances made to their respective organisation will also be investigated. This report will also show a broad range of approaches and ML algorithms tested and used and the different results associated with that. This richness is a testament of the commitment and contribution of all the NSO (National Statistics Offices) involved and their commitment to this project. |
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