reg_mlp | R Documentation |
Creates a regression object that uses the Multi-Layer Perceptron (MLP) method. It wraps the nnet library.
reg_mlp(attribute, size = NULL, decay = 0.05, maxit = 1000)
attribute |
attribute target to model building |
size |
number of neurons in hidden layers |
decay |
decay learning rate |
maxit |
number of maximum iterations for training |
obj
data(Boston)
model <- reg_mlp("medv", size=5, decay=0.54)
# preparing dataset for random sampling
sr <- sample_random()
sr <- train_test(sr, Boston)
train <- sr$train
test <- sr$test
model <- fit(model, train)
test_prediction <- predict(model, test)
test_predictand <- test[,"medv"]
test_eval <- evaluate(model, test_predictand, test_prediction)
test_eval$metrics
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