Kumo allows you to tune your model’s hyperparameters via the model planner, as well as other configurations such as training table splits, sampling, column encoding, training process, neural architecture, and optimization goals, to name a few. With Kumo’s model planner, data scientists can tune their model’s architecture for the dataset, ensuring that their predictive models deliver the best performance.Documentation Index
Fetch the complete documentation index at: https://kumo.ai/docs/llms.txt
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Model Performance