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@@ -271,8 +271,8 @@ examining the loss on the training data. Subject to the size constraint, this
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operation provides an upper bound on the improvement in validation loss.
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A fixed number of rounds is used for optimization which depends on the number of
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-parameters being optimized. The optimitazion starts with random search, then
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-Bayesian Optimisation is performed that is targeting maximum expected
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+parameters being optimized. The optimization starts with random search, then
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+Bayesian optimization is performed that is targeting maximum expected
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improvement. If you override any parameters, then the optimization will
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calculate the value of the remaining parameters accordingly and use the value
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you provided for the overridden parameter. The number of rounds are reduced
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lcawl