我在使用caret中的awtan方法创建预测模型时，训练过程持续失败，出现以下错误：

 model fit failed for Resample04: score=bic, smooth=1 Error : 'lpawnb' is not an exported object from 'namespace:bnclassify'

我使用的是bnclassify版本0.3.4。根据GitHub上的发布说明，看起来lpawnb()在0.3.2版本中被lp()替换了，所以我初步猜测问题是某种遗留的错误（在caret中？在bnclassify中？），导致调用了后者而不是前者。

另一方面，或许是我自己操作有误。以下是一个示例代码：

library(caret)library(bnclassify)data  <- structure(list(var1 = structure(c(2L, 2L, 1L, 2L, 2L, 1L, 2L,  2L, 2L, 2L, 2L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Label = c("0",  "1"), class = "factor"), var2 = structure(c(2L, 1L, 1L, 1L, 2L,  1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 2L, 2L, 1L, 1L, 2L), .Label = c("0",  "1"), class = "factor"), var3 = structure(c(1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L), .Label = c("0",  "1"), class = "factor"), var4 = structure(c(2L, 1L, 1L, 2L, 2L,  1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L), .Label = c("0",  "1"), class = "factor"), var5 = structure(c(2L, 2L, 1L, 1L, 1L,  1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("0",  "1"), class = "factor"), var6 = structure(c(2L, 2L, 1L, 2L, 2L,  1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L), .Label = c("0",  "1"), class = "factor"), var7 = structure(c(1L, 1L, 1L, 1L, 1L,  1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L), .Label = c("0",  "1"), class = "factor"), var8 = structure(c(2L, 1L, 2L, 2L, 2L,  1L, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, 2L, 1L, 2L), .Label = c("0",  "1"), class = "factor"), outcome = structure(c(2L, 1L, 1L, 1L,  2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L ), .Label = c("0", "1"), class = "factor")), .Names = c("var1",  "var2", "var3", "var4", "var5", "var6", "var7", "var8", "outcome" ), row.names = c(NA, 20L), class = "data.frame")  model  <- train(x = data %>% select(-outcome), y = data$outcome, method = 'awtan')# 最终会出现以下错误## 出了问题；所有准确率指标值都缺失：#     Accuracy       Kappa    #  Min.   : NA   Min.   : NA  #  1st Qu.: NA   1st Qu.: NA  #  Median : NA   Median : NA  #  Mean   :NaN   Mean   :NaN  #  3rd Qu.: NA   3rd Qu.: NA  #  Max.   : NA   Max.   : NA  #  NA's   :6     NA's   :6    # 错误：停止# 此外：有50个或更多的警告（使用warnings()查看前50个）# # # > warnings()# 警告信息：# 1: model fit failed for Resample01: score=loglik, smooth=1 Error : 'lpawnb' is not an exported object from 'namespace:bnclassify'# # 2: model fit failed for Resample01: score=bic, smooth=1 Error : 'lpawnb' is not an exported object from 'namespace:bnclassify'# # 3: model fit failed for Resample01: score=aic, smooth=1 Error : 'lpawnb' is not an exported object from 'namespace:bnclassify'

使用相同的数据，我能够使用bnclassify的函数构建模型，所以我猜测这是caret中的一个错误，在调用lpawnb()时应该使用bnclassify::lp()，但我还不清楚如何确认这一点。

在责怪比我聪明得多的包开发者之前，有人能帮我解释一下我可能做错了什么吗？

回答：

看起来CRAN上当前版本的caret，6.0-78，使用bnclassify::lpawnb()定义了awtan模型的拟合函数，而bnclassify已经用lp()替换了它：

getModelInfo('awtan')...     $awtan$fitfunction (x, y, wts, param, lev, last, classProbs, ...) {    dat <- if (is.data.frame(x))         x    else as.data.frame(x)    dat$.outcome <- y    struct <- bnclassify::tan_cl(class = ".outcome", dataset = dat,         score = as.character(param$score))    bnclassify::lpawnb(struct, dat, smooth = param$smooth, trees = 10,         bootstrap_size = 0.5, ...)}...