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Chapter title |
Using Weighted Nearest Neighbor to Benefit from Unlabeled Data
|
---|---|
Chapter number | 10 |
Book title |
Advances in Knowledge Discovery and Data Mining
|
Published by |
Springer, Berlin, Heidelberg, April 2006
|
DOI | 10.1007/11731139_10 |
Book ISBNs |
978-3-54-033206-0, 978-3-54-033207-7
|
Authors |
Kurt Driessens, Peter Reutemann, Bernhard Pfahringer, Claire Leschi |
Mendeley readers
The data shown below were compiled from readership statistics for 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 3% |
Unknown | 33 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 11 | 32% |
Student > Master | 8 | 24% |
Professor > Associate Professor | 6 | 18% |
Student > Doctoral Student | 3 | 9% |
Researcher | 2 | 6% |
Other | 3 | 9% |
Unknown | 1 | 3% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 27 | 79% |
Engineering | 2 | 6% |
Agricultural and Biological Sciences | 1 | 3% |
Mathematics | 1 | 3% |
Arts and Humanities | 1 | 3% |
Other | 0 | 0% |
Unknown | 2 | 6% |