Improved Use of Continuous Attributes in C4.5
Impact in
Classified as
- Authors
- J. R. Quinlan
In The Last Decade
doi.org/10.1613/jair.279 →Countries where authors are citing Improved Use of Continuous Attributes in C4.5
This map shows the geographic impact of Improved Use of Continuous Attributes in C4.5. 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 Improved Use of Continuous Attributes in C4.5 with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Improved Use of Continuous Attributes in C4.5 more than expected).
Fields of papers citing Improved Use of Continuous Attributes in C4.5
This network shows the impact of Improved Use of Continuous Attributes in C4.5. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Improved Use of Continuous Attributes in C4.5.
About Improved Use of Continuous Attributes in C4.5
This paper, published in 1996, received 1.5k indexed citations . Written by J. R. Quinlan covering the research area of Artificial Intelligence, Computational Theory and Mathematics and Information Systems. It is primarily cited by scholars working on Artificial Intelligence (799 citations), Information Systems (436 citations), Computational Theory and Mathematics (213 citations), Computer Vision and Pattern Recognition (187 citations) and Molecular Biology (139 citations). Published in Journal of Artificial Intelligence Research.
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/10.1613/jair.279.