predict.GMDH {GMDH2}

Predicting Using GMDH Algorithm for Binary Classification

Description

This function predicts values based upon a model trained by GMDH.

Usage

## S3 method for class 'GMDH'
predict(object, x, type = "class", ...)

Arguments

object

an object of class "GMDH", created by GMDH.

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.

Value

A vector of predicted values of corresponding classes depending on type specified.

Author(s)

Osman Dag, Erdem Karabulut, Reha Alpar

See Also

GMDH

Examples

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")