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Scandinavian Journal of Forest Research Volume 29, 2014 - Issue 2
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RESEARCH ARTICLE

The k-nearest neighbor technique with local linear regression

Steen MagnussenCanadian Forest Service, Natural Resources Canada, 506 West Burnside Road, Victoria, BCV8Z 1M5, CanadaCorrespondence[email protected]
&
Erkki TomppoThe Finnish Forest Research Institute, PO Box 18 (Jokiniemenkuja 1), VantaaFI-01301, Finland
Pages 120-131 | Received 27 Jun 2013, Accepted 19 Dec 2013, Published online: 28 Jan 2014

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Steen Magnussen & Erkki Tomppo. (2016) Model-calibrated k-nearest neighbor estimators. Scandinavian Journal of Forest Research 31:2, pages 183-193.
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Articles from other publishers (8)

Markus Levy & Filip Naiser. 2019. Software Engineering for Embedded Systems. Software Engineering for Embedded Systems 549 601 .
Jianglin Huang, Jacky Wai Keung, Federica Sarro, Yan-Fu Li, Y.T. Yu, W.K. Chan & Hongyi Sun. (2017) Cross-validation based K nearest neighbor imputation for software quality datasets: An empirical study. Journal of Systems and Software 132, pages 226-252.
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Michael S. Watt, Jonathan P. Dash, Pete Watt & Santosh Bhandari. (2016) Multi-sensor modelling of a forest productivity index for radiata pine plantations. New Zealand Journal of Forestry Science 46:1.
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Jonathan P. Dash, Michael S. Watt, Santosh Bhandari & Pete Watt. (2016) Characterising forest structure using combinations of airborne laser scanning data, RapidEye satellite imagery and environmental variables. Forestry 89:2, pages 159-169.
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Michael S. Watt, Jonathan P. Dash, Santosh Bhandari & Pete Watt. (2015) Comparing parametric and non-parametric methods of predicting Site Index for radiata pine using combinations of data derived from environmental surfaces, satellite imagery and airborne laser scanning. Forest Ecology and Management 357, pages 1-9.
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Alexander MasseyDaniel Mandallaz. (2015) Comparison of classical, kernel-based, and nearest neighbors regression estimators using the design-based Monte Carlo approach for two-phase forest inventories. Canadian Journal of Forest Research 45:11, pages 1480-1488.
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J. P. Dash, H. M. Marshall & B. Rawley. (2015) Methods for estimating multivariate stand yields and errors using k-NN and aerial laser scanning. Forestry 88:2, pages 237-247.
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Andreas Hill, Jochen Breschan & Daniel Mandallaz. (2014) Accuracy Assessment of Timber Volume Maps Using Forest Inventory Data and LiDAR Canopy Height Models. Forests 5:9, pages 2253-2275.
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