predict.KDSNensemble: Predict kernel deep stacking networks ensembles...
In kernDeepStackNet: Kernel Deep Stacking Networks

Description Usage Arguments Details Value Author(s) See Also

Predicts new data with a given kernel deep stacking network ensemble. All levels are applied successively with fixed weights to reproduce results. Note that this function is still experimental.

1 2	## S3 method for class 'KDSNensemble' predict(object, newx, ...)

`object`	Object of class `KDSNensemble`. This object is generated with the function `fitEnsembleKDSN`.
`newx`	New data design matrix, for which predictions are needed. Variables must be in the same order, as the original training data.
`...`	Further arguments to `predict` function.

The data is put through all specified layers of the kernel deep stacking network. The weights are not random, but fixed at the values generated by the fitting process. Examples are given in the help page of fitEnsembleKDSN.

A prediction matrix will be returned. Each row corresponds to one observation and each column is another KDSN ensemble.

Thomas Welchowski welchow@imbie.meb.uni-bonn.de

fitKDSN, fitEnsembleKDSN

kernDeepStackNet documentation built on May 2, 2019, 8:16 a.m.