# altered freq_cut and unique_cut The `options` argument of `step_nzv()` was deprecated in recipes 0.1.7 and is now defunct. i Please use the arguments `freq_cut` and `unique_cut` instead. # Deprecation warning Code recipe(~., data = mtcars) %>% step_nzv(options = list(freq_cut = 95 / 5, unique_cut = 20)) Condition Error: ! The `options` argument of `step_nzv()` was deprecated in recipes 0.1.7 and is now defunct. i Please use the arguments `freq_cut` and `unique_cut` instead. # printing Code print(rec) Output Recipe Inputs: role #variables outcome 1 predictor 4 Operations: Sparse, unbalanced variable filter on x1, x2, x3, x4 --- Code prep(rec) Output Recipe Inputs: role #variables outcome 1 predictor 4 Training data contained 50 data points and no missing data. Operations: Sparse, unbalanced variable filter removed x3, x4 [trained] # empty printing Code rec Output Recipe Inputs: role #variables outcome 1 predictor 10 Operations: Sparse, unbalanced variable filter on <none> --- Code rec Output Recipe Inputs: role #variables outcome 1 predictor 10 Training data contained 32 data points and no missing data. Operations: Sparse, unbalanced variable filter removed <none> [trained] # nzv with case weights Code recipe(~., dat_caseweights_x2) %>% step_nzv(all_predictors(), freq_cut = exp_freq_cut_int) %>% prep() Output Recipe Inputs: role #variables case_weights 1 predictor 4 Training data contained 50 data points and no missing data. Operations: Sparse, unbalanced variable filter removed x4 [weighted, trained] --- Code recipe(~., dat_caseweights_y) %>% step_nzv(all_predictors(), freq_cut = exp_freq_cut_frag - 1e-04) %>% prep() Output Recipe Inputs: role #variables case_weights 1 predictor 4 Training data contained 50 data points and no missing data. Operations: Sparse, unbalanced variable filter removed x3, x4 [ignored weights, trained]
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