Data stacks are tibbles (with some extra attributes) that contain the response value as the first column, and the assessment set predictions for each candidate ensemble member.
tree_frogs_model_st <-# example from stacks vignettestacks() %>%add_candidates(knn_res) %>%add_candidates(lin_reg_res) %>%add_candidates(svm_res)tree_frogs_model_st#> # A data stack with 3 model definitions and 11 candidate members:#> # knn_res: 4 model configurations#> # lin_reg_res: 1 model configuration#> # svm_res: 6 model configurations#> # Outcome: latency (numeric)as_tibble(tree_frogs_model_st)#> # A tibble: 429 x 12#> latency knn_res_1_1 knn_res_1_2 knn_res_1_3 knn_res_1_4 lin_reg_res_1_1#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>#> 1 142 -0.496 -0.478 -0.492 -0.494 114. #> 2 79 -0.381 -0.446 -0.542 -0.553 78.6#> 3 50 -0.311 -0.352 -0.431 -0.438 81.5#> 4 68 -0.312 -0.368 -0.463 -0.473 78.6#> 5 64 -0.496 -0.478 -0.492 -0.494 36.5#> 6 52 -0.391 -0.412 -0.473 -0.482 124. #> 7 39 -0.523 -0.549 -0.581 -0.587 35.2#> 8 46 -0.523 -0.549 -0.581 -0.587 37.1#> 9 137 -0.287 -0.352 -0.447 -0.456 78.8#> 10 73 -0.523 -0.549 -0.581 -0.587 38.8#> # … with 419 more rows, and 6 more variables: svm_res_1_1 <dbl>,#> # svm_res_1_4 <dbl>, svm_res_1_3 <dbl>, svm_res_1_5 <dbl>, svm_res_1_2 <dbl>,#> # svm_res_1_6 <dbl>
