In informed search, each iteration learns from the last, whereas in Grid and Random, modelling is all done at once and then the best is picked. In case for small datasets, GridSearch or RandomSearch would be fast and sufficient. AutoML approaches provide a neat solution to properly select the required hyperparameters that improve the model’s performance.
Originally from KDnuggets https://ift.tt/38LjuUa
source https://365datascience.weebly.com/the-best-data-science-blog-2020/algorithms-for-advanced-hyper-parameter-optimizationtuning
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