| predict_pltr {GPLTR} | R Documentation |
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
Examples
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