Sebastian Raschka • 6/11/2016

Model evaluation, model selection, and algorithm selection in machine learning

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This article explores core concepts in machine learning, including model evaluation, model selection, and algorithm selection. It discusses techniques for estimating a model's generalization performance on unseen data, avoiding overfitting, and comparing different algorithms and hyperparameter settings within a typical machine learning workflow.

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#Machine Learning #Model Selection #Model Evaluation
Model evaluation, model selection, and algorithm selection in machine learning

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