Short neuralGAM summary

Default print method for a neuralGAM object.

# S3 method for class 'neuralGAM'
print(x, ...)

Arguments

x

A neuralGAM object.

...

Additional arguments (currently unused).

Value

Prints a brief summary of the fitted model including:

Distribution family

The distribution family used ("gaussian", "binomial", or "poisson").

Formula

The model formula.

Intercept value

The fitted intercept (\(\eta_0\)).

Mean Squared Error (MSE)

The training MSE of the model.

Training sample size

The number of observations used to train the model.

Author

Ines Ortega-Fernandez, Marta Sestelo.

Examples

# \dontrun{


library(neuralGAM)
dat <- sim_neuralGAM_data()
train <- dat$train
test  <- dat$test

ngam <- neuralGAM(
  y ~ s(x1) + x2 + s(x3),
  data = train,
  num_units = 128,
  family = "gaussian",
  activation = "relu",
  learning_rate = 0.001,
  bf_threshold = 0.001,
  max_iter_backfitting = 10,
  max_iter_ls = 10,
  seed = 1234
)
#> [1] "Initializing neuralGAM..."
#> [1] "BACKFITTING Iteration 1 - Current Err =  0.00314307849443241 BF Threshold =  0.001 Converged =  FALSE"
#> [1] "BACKFITTING Iteration 2 - Current Err =  0.0035904802501205 BF Threshold =  0.001 Converged =  FALSE"
#> [1] "BACKFITTING Iteration 3 - Current Err =  0.0022177874489898 BF Threshold =  0.001 Converged =  FALSE"
#> [1] "BACKFITTING Iteration 4 - Current Err =  0.00198120946126081 BF Threshold =  0.001 Converged =  FALSE"
#> [1] "BACKFITTING Iteration 5 - Current Err =  0.00268658957361894 BF Threshold =  0.001 Converged =  FALSE"
#> [1] "BACKFITTING Iteration 6 - Current Err =  0.00280545783365124 BF Threshold =  0.001 Converged =  FALSE"
#> [1] "BACKFITTING Iteration 7 - Current Err =  0.0019751075608256 BF Threshold =  0.001 Converged =  FALSE"
#> [1] "BACKFITTING Iteration 8 - Current Err =  0.000915071832718818 BF Threshold =  0.001 Converged =  TRUE"
print(ngam)
#> Class: neuralGAM 
#> Family             : gaussian
#> Formula            : y ~ s(x1) + x2 + s(x3)
#> Observations       : 1400
#> Intercept (eta0)   : 4.47201
#> Deviance explained : 90.78%
#> Train MSE          : 1.22241
#> Pred. / Conf. Int. : disabled
# }