Estimating individual tree growth with the k-nearest neighbour and k-Most Similar Neighbour methods
The purpose of this study was to examine the use of non-parametric methods in estimating tree level growth models. In non-parametric methods the growth of a tree is predicted as a weighted average of the values of neighbouring observations. The selection of the nearest neighbours is b...
Main Authors: | Sironen, Susanna, Kangas, Annika, Maltamo, Matti, Kangas, Jyrki |
---|---|
Format: | Article |
Language: | English |
Published: |
Finnish Society of Forest Science
2001-01-01
|
Series: | Silva Fennica |
Online Access: | https://www.silvafennica.fi/article/580 |
Similar Items
-
The Most Similar Neighbour reference in the yield prediction of Pinus kesiya stands in Zambia
by: Maltamo, Matti, et al.
Published: (2001-01-01) -
Reliability of classification and prediction in k-nearest neighbours
by: Villa Medina, Joe Luis
Published: (2013) -
An assessment of three variance estimators for the k-nearest neighbour technique
by: Magnussen, Steen
Published: (2013-01-01) -
k-Nearest Neighbour Classification of Datasets with a Family of Distances
by: Hatko, Stan
Published: (2015) -
OPTIMIZATION OF K-NEAREST NEIGHBOUR TO CATEGORIZE INDONESIAN'S NEWS ARTICLES
by: Afdhalul Ihsan, et al.
Published: (2021-06-01)