如何解决“无法将类强制转换为data.frame?

时间:2019-11-15 05:09:08

标签: r machine-learning regression training-data supervised-learning

第20行出现问题:x3 <- lm(Salary ~ ...

  

as.data.frame.default(data)中的错误:无法将类“ c(“ train”,“ train.formula”)'强制转换为data.frame

如何解决?

attach(Hitters)
Hitters

library(caret)
set.seed(123)
# Define training control
set.seed(123) 
train.control <- trainControl(method = "cv", number = 10)
# Train the model
x2 <- train(Salary ~., data = x, method = "lm",
               trControl = train.control)
# Summarize the results
print(x)
x3 <- lm(Salary ~ poly(AtBat,3) + poly(Hits,3) + poly(Walks,3) + poly(CRuns,3) + poly(CWalks,3) + poly(PutOuts,3), data = x2)
summary(x3)
MSE = mean(x3$residuals^2)
print("Mean Squared Error: ")
print(MSE)

1 个答案:

答案 0 :(得分:0)

首先,如@dcarlson所述,您应该定义x。 其次,x3不返回数据帧。 如果您运行

str(x2)

您将看到lm函数中使用的所有元素都是称为trainingData的数据框的一部分。 因此,如果您打算使用lm函数,请将其用作lm函数中的数据源, x2。 我已经在下面重写了您的代码。

PS我距离R专家还很远,所以如果有人想用这个答案射击,那就继续吧,我总是愿意学习;)

attach(Hitters)
Hitters

library(caret)
set.seed(123)

# Define training control
set.seed(123) 
train.control <- trainControl(method = "cv", number = 10)

# Train the model
x2 <- train(Salary ~., data = x, method = "lm", trControl = train.control)

# Summarize the results
print(x2)
# str(x2) # $trainingData data.frame

x2$trainingData[["AtBat"]]
m <- x2$trainingData

x3 <- lm(Salary ~ poly(AtBat,3) + poly(Hits,3) + poly(Walks,3) + poly(CRuns,3) + poly(CWalks,3) + poly(PutOuts,3), data = m)
summary(x3)
MSE = mean(x3$residuals^2)
cat("Mean Squared Error: ", MSE) # use cat to concatenate text and variable value in one line