Java Deep Learning Cookbook

How it works...

In step 2, we created ContinuousParameterSpace to configure the search space for hyperparameter optimization:

ParameterSpace<Double> learningRateParam = new ContinuousParameterSpace(0.0001,0.01);

In the preceding case, the hyperparameter tuning process will select continuous values in the range (0.0001, 0.01) for the learning rate. Note that arbiter doesn't really automate the hyperparameter tuning process. We still need to specify the range of values or a list of options by which the hyperparameter tuning process takes place. In other words, we need to specify a search space with all the valid values for the tuning process to pick the best combination that can produce the best results. We have also mentioned IntegerParameterSpace ...