TrainIBHM: TrainIBHM

In IBHM: Approximation using the IBHM method

Description

Trains an IBHM model using training data with input variables x and a single output variable y.

Usage

TrainIBHM(x, y, config = ConfigureIBHM())

Arguments

x	Training data input variables. Should be convertible to a matrix with each row corresponding to a single data point.
y	Training data output variable. Should be convertible to a matrix with a single column and the number of rows equal to the number of rows of x.
config	A configuration object created using ConfigureIBHM. Contains settings such as the stop criterion, optimization method parameters etc.

Value

The created model which is an object of class "IBHM".

References

Zawistowski, P. and Arabas, J.: "Benchmarking IBHM method using NN3 competition dataset." In Proc. 6th int. conf. on Hybrid artificial intelligent systems - Vol. 1, HAIS'11, pp 263–270, 2011. Springer-Verlag.

See Also

ConfigureIBHM,summary.IBHM,predict.IBHM

Examples

  # Training data
  x <- seq(-3,3,length.out=400)
  y <- tanh(x)
  
  # A held out validation set for the stop criterion
  x.val <- runif(50,min=-6,max=6)
  y.val <- tanh(x.val)
  
  
  # Training the model using the validation set to prevent overfitting
  m <- TrainIBHM(x,y, 
            ConfigureIBHM(stop.criterion = ValidationSC(x.val, y.val))
       )
                      
  summary(m)
  plot(y.val,predict(m,x.val),asp=1)

IBHM documentation built on May 30, 2017, 4:32 a.m.