DeepAI
Log In Sign Up

Mlr3spatiotempcv: Spatiotemporal resampling methods for machine learning in R

10/25/2021
by   Patrick Schratz, et al.
0

Spatial and spatiotemporal machine-learning models require a suitable framework for their model assessment, model selection, and hyperparameter tuning, in order to avoid error estimation bias and over-fitting. This contribution reviews the state-of-the-art in spatial and spatiotemporal CV, and introduces the R package mlr3spatiotempcv as an extension package of the machine-learning framework mlr3. Currently various R packages implementing different spatiotemporal partitioning strategies exist: blockCV, CAST, kmeans and sperrorest. The goal of mlr3spatiotempcv is to gather the available spatiotemporal resampling methods in R and make them available to users through a simple and common interface. This is made possible by integrating the package directly into the mlr3 machine-learning framework, which already has support for generic non-spatiotemporal resampling methods such as random partitioning. One advantage is the use of a consistent nomenclature in an overarching machine-learning toolkit instead of a varying package-specific syntax, making it easier for users to choose from a variety of spatiotemporal resampling methods. This package avoids giving recommendations which method to use in practice as this decision depends on the predictive task at hand, the autocorrelation within the data, and the spatial structure of the sampling design or geographic objects being studied.

READ FULL TEXT
05/01/2020

DriveML: An R Package for Driverless Machine Learning

In recent years, the concept of automated machine learning has become ve...
12/05/2018

spGARCH: An R-Package for Spatial and Spatiotemporal ARCH models

In this paper, a general overview on spatial and spatiotemporal ARCH mod...
12/17/2021

Deep Learning for Spatiotemporal Modeling of Urbanization

Urbanization has a strong impact on the health and wellbeing of populati...
04/15/2021

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models

We present PyTorch Geometric Temporal a deep learning framework combinin...
03/17/2021

DoubleML – An Object-Oriented Implementation of Double Machine Learning in R

The R package DoubleML implements the double/debiased machine learning f...
05/29/2018

Diagnosing Glaucoma Progression with Visual Field Data Using a Spatiotemporal Boundary Detection Method

Diagnosing glaucoma progression is critical for limiting irreversible vi...
11/22/2022

BASM: A Bottom-up Adaptive Spatiotemporal Model for Online Food Ordering Service

Online Food Ordering Service (OFOS) is a popular location-based service ...