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R 变量'的多名称(nnet)无效类型(闭包);(重量)和#x27;_R_Logistic Regression - Fatal编程技术网

R 变量'的多名称(nnet)无效类型(闭包);(重量)和#x27;

R 变量'的多名称(nnet)无效类型(闭包);(重量)和#x27;,r,logistic-regression,R,Logistic Regression,我试图对我的超市月度门店数据进行多项式逻辑回归。数据如下所示 data.frame': 833233 obs. of 22 variables: $ ProductId : num 105422 105422 143863 170645 397474 ... $ Brand : num NA NA NA NA NA NA NA NA NA NA ... $ Supplier

我试图对我的超市月度门店数据进行多项式逻辑回归。数据如下所示

data.frame':    833233 obs. of  22 variables:
 $ ProductId                      : num  105422 105422 143863 170645 397474 ...
 $ Brand                          : num  NA NA NA NA NA NA NA NA NA NA ...
 $ Supplier                       : Factor w/ 788 levels "[00000] 武商量贩",..: 1 113 265 154 99 99 99 99 99 99 ...
 $ Mode.of.operations             : Factor w/ 3 levels "[1] Distribution",..: 1 1 1 3 2 2 2 2 2 2 ...
 $ Category                       : Factor w/ 27 levels "[01] Fuits and Vegetables",..: 5 5 9 1 22 22 22 22 22 22 ...
 $ Name                           : chr  "土腊肉" "土腊肉" "佳品红金龙" "野山笋" ...
 $ Packaging                      : Factor w/ 108 levels "1","2","3","4",..: 1 1 96 1 1 1 1 1 1 1 ...
 $ Specs                          : Factor w/ 3477 levels "(1*2)","(16+5)ml",..: 3466 3466 2678 3466 92 92 92 92 92 92 ...
 $ Unit                           : Factor w/ 72 levels "1*1","kg","Kg",..: 2 2 57 18 8 8 8 8 8 8 ...
 $ Origin                         : Factor w/ 370 levels "409","China",..: 15 15 15 15 15 15 15 15 15 15 ...
 $ Price                          : num  73.5 73.5 4.4 0 6.64 ...
 $ Sale.quantity                  : num  0 0 464 0 1 0 6 0 0 0 ...
 $ Sale.revenue                   : num  0 0 2784 0 8 ...
 $ Sale.revenue.wo.tax            : num  0 0 2141.54 0 5.68 ...
 $ Profit.margin                  : num  0 0 237.95 0 1.16 ...
 $ Profit.margin.percentage       : num  0 0 0.1 0 0.17 ...
 $ Inventory.turnover.days        : num  0 0 30.2 0 1007 ...
 $ Purchase.amount.wo.tax         : num  0 0 0 0 0 0 0 0 0 0 ...
 $ Inventory.leftover.value.wo.tax: num  111.14 0.22 1066.15 0 181.61 ...
 $ Month                          : Factor w/ 23 levels "1","2","3","4",..: 17 17 17 17 17 17 17 17 17 17 ...
 $ Adjusted.price                 : num  0 0 6 0 8 0 15.9 0 0 0 ...
 $ Wuhan                          : Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ...
我试图通过以下方法找到多项式逻辑回归

model1 = multinom(Mode.of.operations ~ Category+Wuhan+Inventory.turnover.days+Adjusted.price, data = wushang, na.omit)
但我最终犯了以下错误

Error in model.frame.default(formula = Mode.of.operations ~ Category +  : 
  invalid type (closure) for variable '(weights)'
我试图寻找它为什么会发生的答案,但什么也找不到。 如果有人能帮我弄清楚的话。
谢谢

好吧,我解决了你的错误,但我又犯了一个错误。 你必须把论点放在下面:

multinom.glmulti
type(closure)
是一个函数调用。之所以出现这种情况,是因为
multinom(…)
的第三个参数应该是
weights=…
,但您传递的是
na.omit
,它是一个函数。如果要无序使用参数,必须命名它们,如
na.action=na.omit

Im using my own formula with my terms.

```{r}
formula_autom = reformulate(variables_autom_0,"clase") 
res <- glmulti(formula_autom, data=clase_training,
               level=4, fitfunction=multinom.glmulti, crit="aicc", confsetsize=100,na.action=na.omit)