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Bayesian Optimization of Machine Learning Models

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by Max Kuhn: Director, Nonclinical Statistics, Pfizer Many predictive and machine learning models have structural or tuning parameters that cannot be directly estimated from the data. For example, when using K-nearest neighbor model, there is no analytical estimator for K (the number of neighbors). Typically, resampling is used to get good performance estimates of the model for a given set…
Original Post: Bayesian Optimization of Machine Learning Models

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