Question

我正在尝试使用caret和method='glm'训练的回归模型生成PMML。示例模型：

library('caret')

data('GermanCredit')

set.seed(123)

train_rows <- createDataPartition(GermanCredit$Class, p=0.6, list=FALSE)

train_x <- GermanCredit[train_rows, c('Age','ForeignWorker','Housing.Own',
                                      'Property.RealEstate','CreditHistory.Critical') ]
train_y <- as.integer( GermanCredit[train_rows, 'Class'] == 'Good' )

some_glm <- train( train_x, train_y, method='glm', family='binomial', 
                   trControl = trainControl(method='none') )

summary(some_glm$finalModel)

type='rf'对此finalModel library('pmml') pmml(some_glm$finalModel) # Error in if (model$call[[1]] == "glm") { : argument is of length zero # Same problem if I try: some_glm2 <- train( Class ~ Age + ForeignWorker + Housing.Own + Property.RealEstate + CreditHistory.Critical, data=GermanCredit[train_rows, ], family="binomial", method='glm', trControl = trainControl(method='none') ) pmml(some_glm2$finalModel)的未接受回答表明无法使用矩阵界面。

所以我无法使用矩阵或公式语法（我非常确定无论如何都会产生相同的some_glm_base <- glm(Class ~ Age + ForeignWorker + Housing.Own + Property.RealEstate + CreditHistory.Critical, data=GermanCredit[train_rows, ], family="binomial") pmml(some_glm_base) # works）得到pmml：

caret

在基础glm中使用公式接口：

some_glm

对于互操作性，我想继续使用caret。有没有办法将pmml()中生成的glm()转换回$(".bar_item").click(function(){ if($(".bar_item").css('margin-left') === "0px") { $(".bar_item").animate({"margin-left": '-=190'}); } else { $(".bar_item").animate({"margin-left": '+=190'}); } });将接受的格式？或者，如果我想要pmml功能，我是否被迫使用{{1}}构造？

Answer 1

If you set model$call[[1]], the pmml function will work correctly.

So in your case you would want to:

library('pmml')

some_glm$finalModel$call[[1]] <- "glm"
pmml(some_glm$finalModel)

获得由caret :: train产生的glm型模型的pmml表示

1 个答案: