reg_mlp: MLP for regression

In daltoolbox: Leveraging Experiment Lines to Data Analytics

MLP for regression

Description

Creates a regression object that uses the Multi-Layer Perceptron (MLP) method. It wraps the nnet library.

Usage

reg_mlp(attribute, size = NULL, decay = 0.05, maxit = 1000)

Arguments

attribute	attribute target to model building
size	number of neurons in hidden layers
decay	decay learning rate
maxit	number of maximum iterations for training

Value

returns a object of class reg_mlp

Examples

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

daltoolbox documentation built on Nov. 3, 2024, 9:06 a.m.