ts_rf | R Documentation |
Creates a time series prediction object that uses the Random Forest. It wraps the randomForest library.
ts_rf(preprocess = NA, input_size = NA, nodesize = 1, ntree = 10, mtry = NULL)
preprocess |
normalization |
input_size |
input size for machine learning model |
nodesize |
node size |
ntree |
number of trees |
mtry |
number of attributes to build tree |
a ts_rf
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$test)
model <- ts_rf(ts_norm_gminmax(), input_size=4, nodesize=3, ntree=50)
model <- fit(model, x=io_train$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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