在R中使用套索训练模型时，如何解决“错误：优化参数网格应具有列alpha，lambda”？

问：

我正在尝试按照 YouTube 上的本教程学习套索模型：https://www.youtube.com/watch?v=5GZ5BHOugBQ&ab_channel=DavidCaughlin。但是，当我尝试训练模型时，我遇到了一个错误。

Error: The tuning parameter grid should have columns alpha, lambda 

数据集可以在这里找到： https://github.com/davidcaughlin/R-Tutorial-Data-Files/blob/master/lasso.csv

library(readr)
library(caret)
library(glmnet)

df<- read_csv("/Path/lasso.csv")
  
set.seed(1001)

#partition (split) and create index matrix of selected values

index<- createDataPartition(df$y, p = 0.8, list = FALSE, times = 1)

#create test and training df

train_df <- df[index, ] 
trest_df <- df[-index, ]  
  
# specifying k-fold cross validation (10 fold) framework

crlspecs <- trainControl(method = "cv", number = 10,
                         savePredictions = "all")

#specify and train lasso reg model
#create vector of potential lambda values
lambda_vec <- 10^seq(5, -5, length = 500)

set.seed(1001)

#specify lasso regression model to be estimated using traing data 
# and 10-fold cross-validation framework

TunGrid<-expand.grid(alpha=1,labda=lambda_vec)

#installing latest catet package
devtools::install_github('topepo/caret/pkg/caret')
library("caret")

getNamespaceVersion("caret")
version 
"6.0-94" 

#model training
model1 <-  train( y ~ . ,
                  data = train_df,
                  preProcess=c("center","scale"),
                  method="glmnet",
                  tuneGrid=TunGrid,
                  trControl=crlspecs,
                  na.action = na.omit )

如果有人能在这方面提供任何建议，那将是非常有帮助的。