我有一个 Dataframe ，我想用一个特定的预测器集除以大于零的预测器（也来自该特定集）的数量，当我试图将此操作包含在配方中时，它似乎除以了特定集中的预测器总数，忽略了它应该大于零的条件。
示例：

df <- data.frame(matrix(c(16, 8, 4, 2, 32, 16, 8, 4, 0, 32, 16, 8, 0, 0, 32, 16, 0, 0, 0, 32), 4, 5))

  X1 X2 X3 X4 X5
1 16 32  0  0  0
2  8 16 32  0  0
3  4  8 16 32  0
4  2  4  8 16 32

vars <- names(df)[-1]

df_temp <- df %>% 
  mutate(pos_count = rowSums(df %>% select(all_of(vars)) > 0))

df_temp <- df_temp %>% 
  mutate(across(all_of(vars), .fns = ~./pos_count))

lm_recipe <- 
  recipe(X1 ~ X2 + X3 + X4 + X5, data = df_temp) 

lm_model <- 
  linear_reg(penalty = 0) %>%  
  set_engine("glmnet", lower.limits = rep(0, 5), upper.limits = rep(1, 5), intercept = FALSE)

lm_wflow <- 
  workflow() %>% 
  add_model(lm_model) %>%
  add_recipe(lm_recipe)

lm_fit <- fit(lm_wflow,  df_temp)
lm_fit %>% tidy()

  term        estimate penalty
1 (Intercept)   0            0
2 X2            0.492        0
3 X3            0.240        0
4 X4            0.112        0
5 X5            0.0256       0

这似乎或多或少起作用（估计值应为0, 1/2, 1/4, 1/8 and 1/16）。
但是，当我在配方中加入数据准备时，所有预测因子都除以预测因子总数（在本例中为4个）：

lm_recipe <- 
  recipe(X1 ~ X2 + X3 + X4 + X5, data = df) %>% 
  step_mutate(pos_count = sum(all_of(vars) > 0)) %>%
  step_mutate(across(all_of(vars), .fns = ~./pos_count)) 

lm_wflow <- 
  workflow() %>% 
  add_model(lm_model) %>%
  add_recipe(lm_recipe)

lm_fit <- fit(lm_wflow,  df)

lm_fit %>% tidy()

  term        estimate penalty
1 (Intercept)    0           0
2 X2             1           0
3 X3             0.478       0
4 X4             0           0
5 X5             0           0
6 pos_count      0           0

augment(lm_fit, df)

     X1    X2    X3    X4    X5 .pred
1    16    32     0     0     0  8   
2     8    16    32     0     0  7.82
3     4     8    16    32     0  3.91
4     2     4     8    16    32  1.96

我需要怎么改变食谱才能解决这个问题？谢谢!