Treffer: Mastering machine learning for spatial prediction (part 1): Introduction and Overview of Methods

Title:
Mastering machine learning for spatial prediction (part 1): Introduction and Overview of Methods
Authors:
Contributors:
Kompetenzzentrum für nicht-textuelle Materialien
Publisher Information:
OpenGeoHub Foundation
Publication Year:
2020
Document Type:
course material<br />moving image (video)
Language:
English
Accession Number:
edsbas.7AEF96E1
Database:
BASE

Weitere Informationen

(en)Many algorithm driven statistical methods are nowadays used for (spatial) prediction. Participants will get an overview of the different types/families of methods (shrinkage, generalized additive models, tree based methods, neural networks, support vector machines) and different machine learning concepts (bootstrap, boosting, model averaging). Three methods selected from different families (random forest, support vector machines, lasso) are presented in more detail including tuning of model parameters for these models.