Open topepo opened 1 year ago
Somewhat due to randomness; different random numbers may not fail
library(tidymodels) library(brulee) tidymodels_prefer() data(ames, package = "modeldata") ames$Sale_Price <- log10(ames$Sale_Price) set.seed(122) in_train <- sample(1:nrow(ames), 2000) ames_train <- ames[ in_train,] ames_test <- ames[-in_train,] set.seed(1) brulee_linear_reg(x = as.matrix(ames_train[, c("Longitude", "Latitude")]), y = ames_train$Sale_Price, penalty = 0.10, epochs = 10, batch_size = 64, optimizer = "SGD", verbose = TRUE) #> Warning: Current loss in NaN. Training wil be stopped. #> Linear regression #> #> 2,000 samples, 2 features, numeric outcome #> weight decay: 0.1 #> batch size: 64 #> scaled validation loss after 1 epoch: NaN
Created on 2023-11-02 with reprex v2.0.2
Somewhat due to randomness; different random numbers may not fail
Created on 2023-11-02 with reprex v2.0.2