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Identifying Predictors For Energy Poverty.pdf

Identifying_predictors_for_energy_poverty.pdf
Preview of Identifying predictors for energy poverty
🔗 Source: pure.uva.nl
📊 Size: 2.65 MB
📄 Pages: 13 pages
⬇️ Downloads: 69

Summary

Researchers used machine learning to identify predictors for energy poverty in Europe, analyzing a dataset from 11 countries. They found that income, floor area, and household size are significant predictors, with both universal and contextual factors at play. The study recommends increasing and streamlining household data collection to facilitate further research into energy poverty.

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Description

Researchers used machine learning to identify predictors for energy poverty in Europe, analyzing a dataset from 11 countries.

Technical Information

  • File Format: PDF
  • File Size: 2.65 MB
  • Pages: 13
  • Language: EN
  • Total Downloads: 69
  • Last Updated: 1 week ago

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This PDF document about Identifying predictors for energy poverty provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Identifying predictors for energy poverty.

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