Machine learning on small size samples: A synthetic knowledge synthesis
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Abstract
Machine Learning is an increasingly important technology dealing with the growing complexity of the digitalised world. Despite the fact, that we live in a 'Big data' world where, almost 'everything' is digitally stored, there are many real-world situations, where researchers are still faced with small data samples. The present bibliometric knowledge synthesis study aims to answer the research question 'What is the small data problem in machine learning and how it is solved?' The analysis a positive trend in the number of research publications and substantial growth of the research community, indicating that the research field is reaching maturity. Most productive countries are China, United States and United…
Citation impact
243
total citations
- FWCI
- 44.80
- Percentile
- 100%
- References
- 79
Citations per year
Authors
3- PKPeter KokolCorresponding
University of Maribor
- MKMarko Kokol
- SZSašo Zagoranski
Topics & keywords
Topics
Keywords
- Big data
- Data science
- Maturity (psychological)
- Field (mathematics)
- China
- Computer science
- Dimension (graph theory)
- Thematic analysis
UN Sustainable Development Goals
- Partnerships for the goals
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