ts_elm: ELM

In daltoolbox: Leveraging Experiment Lines to Data Analytics

ELM

Description

Creates a time series prediction object that uses the Extreme Learning Machine (ELM). It wraps the elmNNRcpp library.

Usage

ts_elm(preprocess = NA, input_size = NA, nhid = NA, actfun = "purelin")

Arguments

preprocess	normalization
input_size	input size for machine learning model
nhid	ensemble size
actfun	defines the type to use, possible values: 'sig', 'radbas', 'tribas', 'relu', 'purelin' (default).

Value

returns a ts_elm object.

Examples

data(sin_data)
ts <- ts_data(sin_data$y, 10)
ts_head(ts, 3)

samp <- ts_sample(ts, test_size = 5)
io_train <- ts_projection(samp$train)
io_test <- ts_projection(samp$test)

model <- ts_elm(ts_norm_gminmax(), input_size=4, nhid=3, actfun="purelin")
model <- fit(model, x=io_train$input, y=io_train$output)

prediction <- predict(model, x=io_test$input[1,], steps_ahead=5)
prediction <- as.vector(prediction)
output <- as.vector(io_test$output)

ev_test <- evaluate(model, output, prediction)
ev_test

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