| /dports/math/R-cran-recipes/recipes/tests/testthat/ |
| H A D | test_integer.R | 28 rec_trained <- prep(rec, traning = tr_dat) globalVar
30 tr_int <- juice(rec_trained, all_predictors())
31 te_int <- bake(rec_trained, te_dat, all_predictors())
48 rec_trained <- prep(rec, traning = tr_dat) globalVar
50 tr_int <- juice(rec_trained, all_predictors())
51 te_int <- bake(rec_trained, te_dat, all_predictors())
67 rec_trained <- prep(rec, traning = tr_dat) globalVar
69 tr_int <- juice(rec_trained, all_predictors())
70 te_int <- bake(rec_trained, te_dat, all_predictors())
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| H A D | test_log.R | 16 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
17 rec_trans <- bake(rec_trained, new_data = ex_dat)
29 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
30 rec_trans <- bake(rec_trained, new_data = ex_dat)
41 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
42 rec_trans <- bake(rec_trained, new_data = ex_dat)
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| H A D | test_intercept.R | 12 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
13 rec_trans <- bake(rec_trained, new_data = ex_dat)
24 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
25 rec_trans <- bake(rec_trained, new_data = ex_dat)
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| H A D | test_inverse.R | 17 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
18 rec_trans <- bake(rec_trained, new_data = ex_dat)
29 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
30 rec_trans <- bake(rec_trained, new_data = ex_dat)
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| H A D | test_logit.R | 15 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
16 rec_trans <- bake(rec_trained, new_data = ex_dat)
24 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
25 rec_trans <- bake(rec_trained, new_data = ex_dat)
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| H A D | test_BoxCox.R | 52 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
54 rec_trans <- bake(rec_trained, new_data = ex_dat)
56 expect_equal(names(exp_lambda)[!is.na(exp_lambda)], names(rec_trained$steps[[1]]$lambdas))
57 expect_equal(exp_lambda[!is.na(exp_lambda)], rec_trained$steps[[1]]$lambdas, tolerance = .001)
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| H A D | test_YeoJohnson.R | 52 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
53 rec_trans <- bake(rec_trained, new_data = ex_dat)
55 expect_equal(names(exp_lambda)[!is.na(exp_lambda)], names(rec_trained$steps[[1]]$lambdas))
56 expect_equal(exp_lambda[!is.na(exp_lambda)], rec_trained$steps[[1]]$lambdas, tolerance = .001)
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| H A D | test_invlogit.R | 14 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
15 rec_trans <- bake(rec_trained, new_data = ex_dat)
21 expect_equal(exp_tidy_tr, tidy(rec_trained, number = 1))
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| H A D | test_grouped_df.R | 16 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
17 rec_trans <- bake(rec_trained, new_data = ex_dat)
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| H A D | test_sqrt.R | 14 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
15 rec_trans <- bake(rec_trained, new_data = ex_dat)
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| H A D | test_multivariate.R | 13 rec_trained <- prep(rec, training = biomass) globalVar
15 results <- bake(rec_trained, head(biomass))
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| H A D | test_discretized.R | 74 rec_trained <- prep(rec, training = ex_tr) globalVar
75 br <- rec_trained$steps[[1]]$objects$x1$breaks
81 expect_equal(tidy(rec_trained, 1), tidy_exp_tr)
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| H A D | test_hyperbolic.R | 21 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
22 rec_trans <- bake(rec_trained, new_data = ex_dat)
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| H A D | test_geodist.R | 20 rec_trained <- prep(rec, traning = rand_data) globalVar
22 tr_int <- juice(rec_trained, all_predictors())
23 te_int <- bake(rec_trained, rand_data, all_predictors())
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| H A D | test_rm.R | 17 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE) globalVar
18 rec_rm <- bake(rec_trained, new_data = ex_dat)
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| /dports/math/R-cran-recipes/recipes/tests/testthat/_snaps/ |
| H A D | BoxCox.md | 4 rec_trained <- prep(rec, training = ex_dat, verbose = FALSE)
|