Description Usage Arguments Details Value References See Also
Predict new examples by a trained discriminant adaptive neural net.
1 2 |
object |
Object of class |
newdata |
A |
... |
Arguments passed to or from other methods. |
This function is a method for the generic function
predict()
for class "dannet"
. It can be
invoked by calling predict(x)
for an object
x
of the appropriate class, or directly by calling
predict.dannet(x)
regardless of the class of the
object.
In contrast to predict.nnet
predict.dannet
does not have a type
argument. Since dannet
is only suitabe for
classification, both, the predicted posterior
probabilities and the class labels, are returned.
A list
with components:
class |
The predicted
class labels (a |
posterior |
Matrix of class posterior probabilities. |
Hand, D. J., Vinciotti, V. (2003), Local versus global models for classification problems: Fitting models where it matters, The American Statistician, 57(2) 124–130.
Ripley, B. D. (1996) Pattern Recognition and Neural Networks. Cambridge.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
fit <- dannet(Species ~ ., data = iris, wf = "gaussian", bw = 0.5, size = 2, rang = 0.1, decay = 5e-4, maxit = 200) pred <- predict(fit) mean(pred$class != iris$Species)
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