Data notes

Forwarded from Artem Ryblov’s Data Science Weekly (Artem Ryblov)

Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning by Sebastian Raschka

The correct use of model evaluation, model selection, and algorithm selection techniques is vital in academic machine learning research as well as in many industrial settings.
This article reviews different techniques that can be used for each of these three subtasks and discusses the main advantages and disadvantages of each technique with references to theoretical and empirical studies. Further, recommendations are given to encourage best yet feasible practices in research and applications of machine learning.

Link
https://arxiv.org/abs/1811.12808

Navigational hashtags: #armknowledgesharing #armarticles
General hashtags: #machinelearning #ml #modelevaluation #evaluation #selection #cv #crossvalidation

@accelerated_learning

www.tgoop.com/data_notes/76

46 viewsOct 3, 2023 at 15:29

Model Evaluation, Model Selection, and Algorithm Selection in Machine Learning by Sebastian Raschka

The correct use of model evaluation, model selection, and algorithm selection techniques is vital in academic machine learning research as well as in many industrial settings.
This article reviews different techniques that can be used for each of these three subtasks and discusses the main advantages and disadvantages of each technique with references to theoretical and empirical studies. Further, recommendations are given to encourage best yet feasible practices in research and applications of machine learning.

Link
https://arxiv.org/abs/1811.12808

Navigational hashtags: #armknowledgesharing #armarticles
General hashtags: #machinelearning #ml #modelevaluation #evaluation #selection #cv #crossvalidation

@accelerated_learning

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