Using machine learning to assess the livelihood impact of electricity access.
Nathan RatledgeGabe CadamuroBrandon de la CuestaMatthieu StiglerMarshall BurkePublished in: Nat. (2022)
Keyphrases
- machine learning
- economic impact
- decision trees
- short term
- machine learning algorithms
- access control
- electricity consumption
- inductive logic programming
- machine learning methods
- pattern recognition
- data analysis
- data mining
- remote access
- explanation based learning
- artificial intelligence
- supervised learning
- knowledge representation
- database
- computational intelligence
- support vector
- reinforcement learning
- learning tasks
- computational biology
- machine learning approaches
- electric power
- supervised machine learning
- power grid
- long term
- learning algorithm
- natural language