About this document
Comparing Forest Prediction Models by naomi 23 is a document available to read on EtoBox.
This document compares five modeling techniques - linear models, generalized additive models, classification and regression trees, multivariate adaptive regression splines, and artificial neural networks - for predicting forest characteristics in five ecological regions of the western United States using forest inventory data and satellite-based information. The modeling techniques are compared on their ability to predict two discrete (forest/non-forest and timberland/woodland) and four continuous (tree bio
- Author
- naomi 23
- Language
- EN