ts_elm | R Documentation |
Creates a time series prediction object that uses the Extreme Learning Machine (ELM). It wraps the elmNNRcpp library.
ts_elm(preprocess = NA, input_size = NA, nhid = NA, actfun = "purelin")
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). |
a ts_elm
object.
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
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