当为数据使用`aret`时，我得到"Error in terms.formula( formula，data = data)：‘. in formula and no 'data’参数“

Question

我正在尝试使用caret查找对一些数据进行kNN分析的最佳k：

library(tidyverse)
library(caret)

# Read and clean up the data
ugriz  <- read.table("QSOs_1st_50k.dat-mags.dat")
ugriz[ugriz == -999] <- NA
fields <- c('name', 'z','delta_z','NED_class','SDSS_class','no_radio','radio_max','no_UV', 'UV_min',
    'u', 'g', 'r', 'i', 'z_mag', 'I', 'J', 'H', 'K', 'W1', 'SPIT_5',
    'W2', 'SPIT_8', 'W3', 'W4', 'NUV', 'FUV')
names(ugriz) <- fields

sample_n(ugriz, 5)
attach(ugriz)

# Randomly split the dataset into training and testing subsets
set.seed(123) # for reproducible randomness in producing training and test sets
training.samples <- z %>% createDataPartition(p=0.5, list = FALSE)
train.data <- ugriz[training.samples]
test.data <- ugriz[-training.samples]

model <- train(z~., data = train.data, method = "knn",
    trControl = trainControl("cv", number = 10),
    preProcess = c("center","scale"),
    tuneLength = 10)

我的目标是测试z对列'u'，'g'，'r'，'I'，'z_mag'，'i'，'J'，'H'，'K'，'W1'，'SPIT_5'，'W2'，'SPIT_8'，'W3'，'W4'，'NUV'，'FUV‘的大小的预测值，但我总是遇到错误

Error in terms.formula(formula, data = data) : 
  '.' in formula and no 'data' argument

如果我将公式改为如下所示

model <- train(z~u, data = train.data, method = "knn",
    trControl = trainControl("cv", number = 10),
    preProcess = c("center","scale"),
    tuneLength = 10) # Gives error

我得到了

Error in eval(predvars, data, env) : 
  invalid 'envir' argument of type 'character'

我使用的是RStudio 1.3.959版本，而R版本是4.0.0。在谷歌上搜索错误，我会在neuralnet中找到相同错误的链接，但在caret中什么都没有。Here它看起来像是某些早期版本的R中有一个bug。

是什么导致了这个错误？

Answer 1

您在数据分区中犯了错误。您在training.samples后面漏掉了一个"，“。由于您没有提供任何数据，我使用的是iris数据

library(caret)
library(tidyverse)
# Randomly split the dataset into training and testing subsets
set.seed(123) # for reproducible randomness in producing training and test sets
training.samples <- createDataPartition(iris$Species ,p=0.5, list = FALSE)
train.data <- iris[training.samples,]
test.data <- iris[-training.samples, ]

train(Species~Sepal.Length, data = train.data, method = "knn",
      trControl = trainControl("cv", number = 10),
      preProcess = c("center","scale"),
      tuneLength = 10)

它不会给我任何错误。