predict.GMDH | R Documentation |
This function predicts values based upon a model trained by GMDH
.
## S3 method for class 'GMDH' predict(object, x, type = "class", ...)
object |
an object of class |
x |
a matrix containing the new input data. |
type |
a character string to return predicted output. If type = "class", the function returns the predicted classes. If type = "probability", it returns the predicted probabilities. Default is set to "class". |
... |
currently not used. |
A vector of predicted values of corresponding classes depending on type specified.
Osman Dag, Erdem Karabulut, Reha Alpar
GMDH
library(GMDH2) library(mlbench) data(BreastCancer) data <- BreastCancer # to obtain complete observations completeObs <- complete.cases(data) data <- data[completeObs,] x <- data.matrix(data[,2:10]) y <- data[,11] seed <- 12345 set.seed(seed) nobs <- length(y) # to split train, validation and test sets indices <- sample(1:nobs) ntrain <- round(nobs*0.6,0) nvalid <- round(nobs*0.2,0) ntest <- nobs-(ntrain+nvalid) train.indices <- sort(indices[1:ntrain]) valid.indices <- sort(indices[(ntrain+1):(ntrain+nvalid)]) test.indices <- sort(indices[(ntrain+nvalid+1):nobs]) x.train <- x[train.indices,] y.train <- y[train.indices] x.valid <- x[valid.indices,] y.valid <- y[valid.indices] x.test <- x[test.indices,] y.test <- y[test.indices] set.seed(seed) # to construct model via GMDH algorithm model <- GMDH(x.train, y.train, x.valid, y.valid) # to obtain predicted classes for test set predict(model, x.test, type = "class") # to obtain predicted probabilities for test set predict(model, x.test, type = "probability")
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