getNetDefinition: Get the Net# definition from a trained neural network model

Returns the Net# definition from a trained neural network model.

Usage

  getNetDefinition(model, getWeights = TRUE)

Arguments

model

The previously trained neural network model.

getWeights

If TRUE, the weights are included in the returned Net# definition.

Details

Returns the Net# definition from a trained neural network model. It is useful for implementing a form of continued training, where the initial weights of the model are obtained from a previously trained model. Because only the weights are initialized from the trained model (but not gradients, momentum etc.), the training is not resumed where it was left at the end of training of the first model.

Value

A character string containing the Net# definition.

Author(s)

Microsoft Corporation Microsoft Technical Support

Examples

 # Train a neural network on the iris dataset for 10 iterations.
 model1 <- rxNeuralNet(
     formula = Species~Sepal.Length + Sepal.Width + Petal.Length + Petal.Width, 
     data = iris, 
     numHiddenNodes=10, 
     type="multi", 
     numIterations=10, 
     optimizer=adaDeltaSgd())

 # Train another neural network on the iris dataset, initializing the topology and weights
 # from the previously trained model.
 model2 <- rxNeuralNet(
     formula = Species~Sepal.Length + Sepal.Width + Petal.Length + Petal.Width, 
     data = iris, 
     netDefinition=getNetDefinition(model1), 
     type="multi", 
     numIterations=10, 
     optimizer = adaDeltaSgd())