Neural network studies. 1. Comparison of overfitting and overtraining
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- Journal of Chemical Information and Computer Sciences
In The Last Decade
doi.org/10.1021/ci00027a006 →Countries where authors are citing Neural network studies. 1. Comparison of overfitting and overtraining
This map shows the geographic impact of Neural network studies. 1. Comparison of overfitting and overtraining. 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 Neural network studies. 1. Comparison of overfitting and overtraining with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neural network studies. 1. Comparison of overfitting and overtraining more than expected).
Fields of papers citing Neural network studies. 1. Comparison of overfitting and overtraining
This network shows the impact of Neural network studies. 1. Comparison of overfitting and overtraining. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Neural network studies. 1. Comparison of overfitting and overtraining.
About Neural network studies. 1. Comparison of overfitting and overtraining
This paper, published in 1995, received 531 indexed citations . Written by Igor V. Tetko, David J. Livingstone and Alexander I. Luik covering the research area of Artificial Intelligence. It is primarily cited by scholars working on Computational Theory and Mathematics (106 citations), Artificial Intelligence (104 citations) and Molecular Biology (71 citations). Published in Journal of Chemical Information and Computer Sciences.
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.
This paper is also available at doi.org/10.1021/ci00027a006.