public class DeepLearning extends hex.SupervisedModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>
| Modifier and Type | Class and Description |
|---|---|
class |
DeepLearning.DeepLearningDriver |
_nclass, _response, _response_key, _vresponse, _vresponse_key| Constructor and Description |
|---|
DeepLearning(DeepLearningModel.DeepLearningParameters parms) |
| Modifier and Type | Method and Description |
|---|---|
hex.Model.ModelCategory[] |
can_build() |
void |
init(boolean expensive)
Initialize the ModelBuilder, validating all arguments and preparing the
training frame.
|
hex.schemas.ModelBuilderSchema |
schema() |
water.Job<DeepLearningModel> |
trainModel()
Start the DeepLearning training Job on an F/J thread.
|
clearInitState, createModelBuilder, error_count, error, getAlgo, getModelBuilder, getModelBuilderName, getModelBuilders, getModelClass, hide, info, registerModelBuilder, train, valid, validationErrors, warncancel, cancel, checksum_impl, dest, done, failed, get, isCancelledOrCrashed, isDone, isRunning, isRunning, isStopped, jobs, msec, onCancelled, progress, remove_impl, start, update, updatepublic DeepLearning(DeepLearningModel.DeepLearningParameters parms)
public hex.Model.ModelCategory[] can_build()
can_build in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>public hex.schemas.ModelBuilderSchema schema()
schema in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>public water.Job<DeepLearningModel> trainModel()
trainModel in class hex.ModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>public void init(boolean expensive)
init in class hex.SupervisedModelBuilder<DeepLearningModel,DeepLearningModel.DeepLearningParameters,DeepLearningModel.DeepLearningModelOutput>