An Optimal Sample Data Usage Strategy to Minimize Overfitting and Underfitting Effects in Regression Tree Models Based on Remotely-Sensed Data

Regression tree models have been widely used for remote sensing-based ecosystem mapping. Improper use of the sample data (model training and testing data) may cause overfitting and underfitting effects in the model. The goal of this study is to develop an optimal sampling data usage strategy for any...

Full description

Saved in:

Bibliographic Details
Published in:	Remote sensing (Basel, Switzerland) Vol. 8; no. 11; p. 943
Main Authors:	Gu, Yingxin, Wylie, Bruce, Boyte, Stephen, Picotte, Joshua, Howard, Daniel, Smith, Kelcy, Nelson, Kurtis
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01.11.2016
Subjects:	Accuracy Case studies Climate change Cubist optimization data mining Datasets Ecosystem models Ecosystems Environment models Geology Landsat Mathematical models MODIS NDVI Optimization overfitting Python scripts Regression analysis regression tree mapping model Remote sensing Software Strategy Training Trends underfitting United States > US
ISSN:	2072-4292, 2072-4292
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!