The relationship between Precision-Recall and ROC curves2006 · 4.0k citations
What are hit papers?
Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if any of the following hold:
it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the
threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.
This map shows the geographic impact of Mark Goadrich'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 Mark Goadrich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Goadrich more than expected).
This network shows the impact of papers produced by Mark Goadrich. 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 Mark Goadrich. The network helps show where Mark Goadrich may publish in the future.
Co-authors
The 7 scholars most cited alongside Mark Goadrich, 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 Mark GoadrichLine = papers co-authored togetherMark Goadrich links everyone, so they are left out of the graph.
All Works
14 of 14 papers shown
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Work
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The relationship between Precision-Recall and ROC curves
Mark Goadrich is a scholar working on Information Systems, Artificial Intelligence, Computer Science Applications, Molecular Biology and General Health Professions, having authored 14 papers that have together received 4.1k indexed citations. Recurring topics across this work include Teaching and Learning Programming (4 papers), Natural Language Processing Techniques (3 papers), Data Mining Algorithms and Applications (3 papers), Genetics, Bioinformatics, and Biomedical Research (2 papers), Artificial Intelligence in Games (2 papers), Mobile Learning in Education (2 papers), Hermeneutics and Narrative Identity (1 paper) and Semantic Web and Ontologies (1 paper). The work is most often cited by research in Artificial Intelligence (1.6k citations), Computer Vision and Pattern Recognition (580 citations), Signal Processing (289 citations), Health Information Management (125 citations) and Software (79 citations). Mark Goadrich has collaborated with scholars based in United States. Frequent co-authors include Jesse Davis, Michael P. Rogers, Jude Shavlik, Matthew C. Jadud, S. Monisha Pulimood, Michael Goldweber and Juan Rodríguez. Their work appears in journals such as The FASEB Journal, Machine Learning, Biochemistry and Molecular Biology Education, Journal of computing sciences in colleges and Lirias (KU Leuven).
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incomplete records, variations in author disambiguation, differences in journal indexing, and
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