![]() ![]() ![]() If an analysis of predictor importance is your goal. If there are predictors that have relatively fewer distinct values than other predictors, for example, if the predictor data set is heterogeneous. | | result | log(1+loss) | runtime | (observed) | (estim.) | ycles | | | | Iter | Eval | Objective: | Objective | BestSoFar | BestSoFar | NumLearningC-| LearnRate | MaxNumSplits | The optimal values obtained by using 'OptimizeHyperparameters' can be different from those obtained using manual search. When you specify 'OptimizeHyperparameters', the software finds optimal parameters automatically using Bayesian optimization. Instead of searching optimal values manually by using the cross-validation option ( 'KFold') and the kfoldLoss function, you can use the 'OptimizeHyperparameters' name-value pair argument. To predict the fuel economy of a car given its number of cylinders, volume displaced by the cylinders, horsepower, and weight, you can pass the predictor data and MdlFinal to predict. ReasonForTermination: 'Terminated normally after completing the requested number of training cycles.' ![]()
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