predict.nn: Neural network prediction

In neuralnet: Training of Neural Networks

Description

Prediction of artificial neural network of class nn, produced by neuralnet().

Usage

## S3 method for class 'nn'
predict(object, newdata, rep = 1, all.units = FALSE, ...)

Arguments

object	Neural network of class nn.
newdata	New data of class data.frame or matrix.
rep	Integer indicating the neural network's repetition which should be used.
all.units	Return output for all units instead of final output only.
...	further arguments passed to or from other methods.

Value

Matrix of predictions. Each column represents one output unit. If all.units=TRUE, a list of matrices with output for each unit.

Author(s)

Marvin N. Wright

Examples

library(neuralnet)

# Split data
train_idx <- sample(nrow(iris), 2/3 * nrow(iris))
iris_train <- iris[train_idx, ]
iris_test <- iris[-train_idx, ]

# Binary classification
nn <- neuralnet(Species == "setosa" ~ Petal.Length + Petal.Width, iris_train, linear.output = FALSE)
pred <- predict(nn, iris_test)
table(iris_test$Species == "setosa", pred[, 1] > 0.5)

# Multiclass classification
nn <- neuralnet((Species == "setosa") + (Species == "versicolor") + (Species == "virginica")
                 ~ Petal.Length + Petal.Width, iris_train, linear.output = FALSE)
pred <- predict(nn, iris_test)
table(iris_test$Species, apply(pred, 1, which.max))

neuralnet documentation built on May 2, 2019, 9:17 a.m.