[英]generating tuning parameter for Caret in R
I've been trying to use the caret package to do k-folds validation of a model. 我一直在尝试使用插入符号包对模型进行k折验证。 I've run lm() to some success, but when I try and do it with caret it fails.
我已经运行lm()取得了一些成功,但是当我尝试用插入符号执行操作时,它失败了。 steps:
脚步:
train_control <- trainControl(method="cv", number=10)
grid <- expand.grid(.fL=c(0), .usekernel=c(FALSE))
model <- train(FantasyPTS ~ Shoots + Height + Weight + Birthyear +
age + Draft_Year + Overall_Draft_Num + Draft_Team + Draft_Age +
GAA + SVPCT + GSAA + QS + QS. + RBS + GPS, data=nhlgoalies, trControl=train_control, method="lm", tuneGrid=grid)
results in 结果是
Error in train.default(x, y, weights = w, ...) :
The tuning parameter grid should have columns intercept
my understanding was always that the model itself should generate the intercept. 我的理解始终是模型本身应该生成拦截。 I know from reading the docs it needs the parameter intercept but I don't know how to generate it before the model itself is created?
通过阅读文档,我知道它需要参数拦截,但是我不知道如何在创建模型本身之前生成它?
You dont give a link to a dataset, so I generate my one for example. 您没有提供指向数据集的链接,因此,例如,我生成了一个。
## Make data
ncol <- 3
Xs <- matrix(rnorm(300*ncol), nrow = 300, ncol = ncol) %>% as.tibble()
Yvec <- rnorm(300)
train_control <- trainControl(method="cv", number=10)
## Fit lm model using train
fit <- train(x= Xs, y = Yvec, method = "lm",trControl = train_control)
So you just don't need to specify tuneGrid
parameter and will be ok. 因此,您只需要指定
tuneGrid
参数就可以了。
声明:本站的技术帖子网页,遵循CC BY-SA 4.0协议,如果您需要转载,请注明本站网址或者原文地址。任何问题请咨询:yoyou2525@163.com.