Toward optimal feature selection

964 indexed citations
published 1996
Journal
International Conference on Machine Learning

In The Last Decade

doi.org/w4345633 →

Countries where authors are citing Toward optimal feature selection

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This map shows the geographic impact of Toward optimal feature selection. 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 Toward optimal feature selection with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Toward optimal feature selection more than expected).

Fields of papers citing Toward optimal feature selection

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Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Toward optimal feature selection. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Toward optimal feature selection.

About Toward optimal feature selection

This paper, published in 1996, received 964 indexed citations . Written by Daphne Koller and Mehran Sahami covering the research area of Artificial Intelligence, Computational Theory and Mathematics and Computer Vision and Pattern Recognition. It is primarily cited by scholars working on Artificial Intelligence (611 citations), Computer Vision and Pattern Recognition (330 citations), Information Systems (207 citations), Molecular Biology (189 citations) and Computational Theory and Mathematics (98 citations). Published in International Conference on Machine Learning.

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/w4345633.

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