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Institution

University of Waikato

EducationHamilton, New Zealand
About: University of Waikato is a education organization based out in Hamilton, New Zealand. It is known for research contribution in the topics: Population & Aotearoa. The organization has 5185 authors who have published 16330 publications receiving 493066 citations. The organization is also known as: Te Whare Wānanga o Waikato & Waikato University.


Papers
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Journal ArticleDOI
TL;DR: This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.
Abstract: More than twelve years have elapsed since the first public release of WEKA. In that time, the software has been rewritten entirely from scratch, evolved substantially and now accompanies a text on data mining [35]. These days, WEKA enjoys widespread acceptance in both academia and business, has an active community, and has been downloaded more than 1.4 million times since being placed on Source-Forge in April 2000. This paper provides an introduction to the WEKA workbench, reviews the history of the project, and, in light of the recent 3.6 stable release, briefly discusses what has been added since the last stable version (Weka 3.4) released in 2003.

19,603 citations

Journal ArticleDOI
TL;DR: In this paper, Heaton, AG Hogg, KA Hughen, KF Kaiser, B Kromer, SW Manning, RW Reimer, DA Richards, JR Southon, S Talamo, CSM Turney, J van der Plicht, CE Weyhenmeyer
Abstract: Additional co-authors: TJ Heaton, AG Hogg, KA Hughen, KF Kaiser, B Kromer, SW Manning, RW Reimer, DA Richards, JR Southon, S Talamo, CSM Turney, J van der Plicht, CE Weyhenmeyer

13,605 citations

Journal ArticleDOI
01 Mar 2002
TL;DR: This presentation discusses the design and implementation of machine learning algorithms in Java, as well as some of the techniques used to develop and implement these algorithms.
Abstract: 1. What's It All About? 2. Input: Concepts, Instances, Attributes 3. Output: Knowledge Representation 4. Algorithms: The Basic Methods 5. Credibility: Evaluating What's Been Learned 6. Implementations: Real Machine Learning Schemes 7. Moving On: Engineering The Input And Output 8. Nuts And Bolts: Machine Learning Algorithms In Java 9. Looking Forward

5,936 citations

Journal ArticleDOI
TL;DR: This review covers the literature published in 2014 for marine natural products, with 1116 citations referring to compounds isolated from marine microorganisms and phytoplankton, green, brown and red algae, sponges, cnidarians, bryozoans, molluscs, tunicates, echinoderms, mangroves and other intertidal plants and microorganisms.

4,649 citations

Journal ArticleDOI
TL;DR: In this paper, a new calibration curve for the conversion of radiocarbon ages to calibrated (cal) ages has been constructed and internationally ratified to replace IntCal98, which extended from 0-24 cal kyr BP (Before Present, 0 cal BP = AD 1950).
Abstract: A new calibration curve for the conversion of radiocarbon ages to calibrated (cal) ages has been constructed and internationally ratified to replace IntCal98, which extended from 0-24 cal kyr BP (Before Present, 0 cal BP = AD 1950). The new calibration data set for terrestrial samples extends from 0-26 cal kyr BP, but with much higher resolution beyond 11.4 cal kyr BP than IntCal98. Dendrochronologically-dated tree-ring samples cover the period from 0-12.4 cal kyr BP. Beyond the end of the tree rings, data from marine records (corals and foraminifera) are converted to the atmospheric equivalent with a site-specific marine reservoir correction to provide terrestrial calibration from 12.4-26.0 cal kyr BP. A substantial enhancement relative to IntCal98 is the introduction of a coherent statistical approach based on a random walk model, which takes into account the uncertainty in both the calendar age and the 14C age to calculate the underlying calibration curve (Buck and Blackwell, this issue). The tree-ring data sets, sources of uncertainty, and regional offsets are discussed here. The marine data sets and calibration curve for marine samples from the surface mixed layer (Marine04) are discussed in brief, but details are presented in Hughen et al. (this issue a). We do not make a recommendation for calibration beyond 26 cal kyr BP at this time; however, potential calibration data sets are compared in another paper (van der Plicht et al., this issue).

3,737 citations


Authors

Showing all 5295 results

NameH-indexPapersCitations
Peter Zoller13473476093
Noah Fierer114311100010
Yigong Shi10624848257
Chris Ryan9597134388
Brian R. Flay8932526390
Shinichi Nakagawa8843939873
Scott Rozelle8778930543
James Chapman8248336468
Diana H. Wall7825032453
Ian H. Witten7644581473
Ian J. Bateman7536121339
James Guthrie7544429705
Gerard J. Milburn7450129565
Christian M. Ringle7420768196
David Hopkins7333922807
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202349
2022187
2021963
2020912
2019855
2018861