John F. Elder

82 papers receiving 3.3k citations

John F. Elder's Hit Papers

Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions 2010 · 386 citations
3860+10+20Years since publication100200300400500

Peers

John F. Elder
Comparison fields: 5 of 195
  • Environmental Chemistry 277
  • Ecology 648
  • Health, Toxicology and Mutagenesis 290
  • Nature and Landscape Conservation 252
  • Pollution 229
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Countries citing papers authored by John F. Elder

Since Specialization
Citations

This map shows the geographic impact of John F. Elder's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by John F. Elder with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John F. Elder more than expected).

Fields of papers citing papers by John F. Elder

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John F. Elder. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by John F. Elder. The network helps show where John F. Elder may publish in the future.

Co-authors

The 25 scholars most cited alongside John F. Elder, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with John F. Elder Line = papers co-authored together John F. Elder links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 91 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Handbook of Statistical Analysis and Data Mining Applications
Hit paper breakdown →
2009542
2
Concerted Evolution of Repetitive DNA Sequences in Eukaryotes
Hit paper breakdown →
1995529
3
Ensemble Methods in Data Mining: Improving Accuracy Through Combining Predictions
Hit paper breakdown →
2010386
4 2010165
5 1996154
6 1991136
7 2000135
8 1990112
9
A statistical perspective on knowledge discovery in databases
199699
10 198891
11 201076
12 199273
13 200269
14 197867
15 200661
16 200059
17 198557
18 197956
19 199849
20 199445

About John F. Elder

John F. Elder is a scholar working on Artificial Intelligence, Information Systems, Ecology, Environmental Chemistry and Water Science and Technology, having authored 91 papers that have together received 3.6k indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (15 papers), Neural Networks and Applications (13 papers), Soil and Water Nutrient Dynamics (12 papers), Water Quality and Resources Studies (12 papers), Fish Ecology and Management Studies (7 papers), Aquatic Ecosystems and Phytoplankton Dynamics (7 papers), Genetic diversity and population structure (7 papers) and Machine Learning and Data Classification (7 papers). The work is most often cited by research in Environmental Chemistry (277 citations), Ecology (648 citations), Health, Toxicology and Mutagenesis (290 citations), Nature and Landscape Conservation (252 citations) and Pollution (229 citations). John F. Elder has collaborated with scholars based in United States, Netherlands and Japan. Frequent co-authors include Bruce J. Turner, Giovanni Seni, Robert Nisbet, Gary Miner, Robert Dolan, Michael S. Fenster, Thomas F. Laughlin, H.C. Mattraw, Alexander J. Horne and Isaac J. Schlosser. Their work appears in journals such as Proceedings of the National Academy of Sciences, The Quarterly Review of Biology, Evolution, Ecology and JAWRA Journal of the American Water Resources Association.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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