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...

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Veröffentlicht in:	Remote sensing (Basel, Switzerland) Jg. 8; H. 11; S. 943
Hauptverfasser:	Gu, Yingxin, Wylie, Bruce, Boyte, Stephen, Picotte, Joshua, Howard, Daniel, Smith, Kelcy, Nelson, Kurtis
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.11.2016
Schlagworte:	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-Zugang:	Volltext
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