make predictions from a "gcdnet" object.
Similar to other predict methods, this functions predicts fitted values and class labels from a fitted
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matrix of new values for
value(s) of the penalty parameter
type of prediction required.
Not used. Other arguments to predict.
s is the new vector at which predictions are requested. If
s is not in the lambda sequence used for fitting the model, the
predict function will use linear interpolation to make predictions. The new values are interpolated using a fraction of predicted values from both left and right
The object returned depends on type.
Yi Yang and Hui Zou
Maintainer: Yi Yang <firstname.lastname@example.org>
Yang, Y. and Zou, H. (2012), "An Efficient Algorithm for Computing The HHSVM and Its Generalizations," Journal of Computational and Graphical Statistics, 22, 396-415.
Friedman, J., Hastie, T., and Tibshirani, R. (2010), "Regularization paths for generalized
linear models via coordinate descent," Journal of Statistical Software, 33, 1.
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