predict_pltr: prediction

In GPLTR: Generalized Partially Linear Tree-Based Regression Model

prediction

Description

prediction on new features using a pltr tree and the name of the confounding variable

Usage

predict_pltr(xtree, xdata, Y.name, X.names, newdata, type = "response",
              family = 'binomial', thresshold = seq(0.1, 0.9, by = 0.1))

Arguments

xtree	a tree obtained with the pltr procedure
xdata	the dataframe used to learn the pltr model
Y.name	the name of the main variable
X.names	the names of the confounding variables
newdata	the new data with all the predictors and the dependent variable
type	the type of prediction
family	the glm family considered
thresshold	the thresshold value to consider for binary prediction. It could be a vector, helping to compute the AUC

Value

A list of two element

predict_glm	the predicted vector, depending on the family used. For the binomial family with a vector of thresshold, a matrix with each column corresponding to a thresshold value
ERR_PRED	either the prediction error of the pltr procedure on the test set or a vector of prediction error when the family is binomial with a vector of thresshold values

Author(s)

Cyprien Mbogning

References

Mbogning, C., Perdry, H., Toussile, W., Broet, P.: A novel tree-based procedure for deciphering the genomic spectrum of clinical disease entities. Journal of Clinical Bioinformatics 4:6, (2014)

See Also

pltr.glm, predict.glm

Examples

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GPLTR documentation built on Aug. 27, 2023, 1:06 a.m.