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library(tidymodels)
# requires brulee; make sure to load it after install to get extra downloads
set.seed(1)
mlp(hidden_units=5, epochs=100) %>%
set_engine("brulee", stop_iter=5) %>%
set_mode("regression") %>%
fit(price~latitude+longitude, data=Sacramento)
#> Warning: The following arguments cannot be manually modified and were removed:#> stop_iter.#> parsnip model object#> #> Multilayer perceptron#> #> relu activation#> 5 hidden units, 21 model parameters#> 932 samples, 2 features, numeric outcome #> weight decay: 0.001 #> dropout proportion: 0 #> batch size: 839 #> learn rate: 0.01 #> scaled validation loss after 8 epochs: 1.03# based on "loss after X epochs" it is actually working
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Created on 2024-01-16 with reprex v2.0.2
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