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Developing a modular and generalizable modeling framework for wheat yield prediction
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Machine learning technology for early prediction of grain yield at the field scale: A systematic review
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Optical vegetation indices for monitoring terrestrial ecosystems globally
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Cross‐validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure
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Climatic and technological ceilings for C hinese rice stagnation based on yield gaps and yield trend pattern analysis
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Regularization and Variable Selection Via the Elastic Net
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Harvest index: a review of its use in plant breeding and crop physiology
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Food Security: The Challenge of Feeding 9 Billion People
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Detecting Novel Associations in Large Data Sets
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The Lack of A Priori Distinctions Between Learning Algorithms
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Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations
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mlr3spatiotempcv: Spatiotemporal Resampling Methods for 'mlr3'
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mlr3verse: Easily Install and Load the 'mlr3' Package Family
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Rtsne: T-Distributed Stochastic Neighbor Embedding using a Barnes-Hut Implementation
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On a Method to Measure Supervised Multiclass Model’s Interpretability: Application to Degradation Diagnosis (Short Paper)
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XGBoost: A Scalable Tree Boosting System
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SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty
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An introduction to variable and feature selection
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