Train function from R caret package error: "Something is wrong; all the Accuracy metric values are missing"

Question

我想运行 logreg 回归。运行在 R:

上设置我的代码后，我收到以下错误

出了点问题；缺少所有准确度指标值：

    Accuracy       Kappa    
 Min.   : NA   Min.   : NA  
 1st Qu.: NA   1st Qu.: NA  
 Median : NA   Median : NA  
 Mean   :NaN   Mean   :NaN  
 3rd Qu.: NA   3rd Qu.: NA  
 Max.   : NA   Max.   : NA  
 NA's   :9     NA's   :9    
Error in train.default(x, y, weights = w, ...) : Stopping
In addition: There were 19 warnings (use warnings() to see them)

这是我的代码：

## Data
donner <- read.delim("http://web.as.uky.edu/statistics/users/pbreheny/760/data/donner.txt")
set.seed(1234)
library(caret)
donner$Age <- as.numeric(donner$Age)
donner$Status <- as.factor(donner$Status)  
donner$Sex <- as.numeric(donner$Sex) 
splitIndex <- createDataPartition(donner$Status, p = .80, list = FALSE, times = 1)
trainDF <- donner[splitIndex,]
testDF <- donner[-splitIndex,]
ctrl <- trainControl(method = "cv", number = 2)
logregmodel <- train(Status ~ ., data = donner, method = "logreg", trControl = ctrl)

编辑 1：

我将状态更改为二进制（0 和 1），但仍然有一些错误。这是新代码：

## Data
donner <- read.delim("http://web.as.uky.edu/statistics/users/pbreheny/760/data/donner.txt")
set.seed(1234)
library(caret)
donner$Age <- as.numeric(donner$Age)
donner$Status <- as.integer(donner$Status)-1  
donner$Sex <- as.numeric(donner$Sex)-1 
splitIndex <- createDataPartition(donner$Status, p = .80, list = FALSE, times = 1)
trainDF <- donner[splitIndex,]
testDF <- donner[-splitIndex,]
ctrl <- trainControl(method = "cv", number = 2)
donner$Status <- as.factor(donner$Status)
logregmodel <- train(Status ~ ., data = donner, method = "logreg", trControl = ctrl)

Answer 1

只是需要修复您的数据。逻辑回归——这就是我假设你想要的，因为你调用了逻辑回归 (logreg) 方法，如果你想要像 logit 模型这样的其他东西，那么整个问题都不重要，这会从一开始就不会给你错误 - 仅适用于二进制变量 and 它不理解 1 和 2 可以表示二进制数据。它需要文字 0 和 1。

donner <- read.delim("http://web.as.uky.edu/statistics/users/pbreheny/760/data/donner.txt")
set.seed(1234)
library(caret)
donner$Age <- as.numeric(donner$Age)
donner$Status <- as.factor(donner$Status)  
donner$Sex <- as.numeric(donner$Sex) 
splitIndex <- createDataPartition(donner$Status, p = .80, list = FALSE, times = 1)
trainDF <- donner[splitIndex,]
testDF <- donner[-splitIndex,]
ctrl <- trainControl(method = "cv", number = 3)
donner$Status <- as.character(donner$Status)
donner$Status[!donner$Status == "Survived"] <- 0
donner$Status[donner$Status == "Survived"] <- 1
donner$Age_gr_mean <- 0
donner$Age_gr_mean[donner$Age_gr_mean > mean(donner$Age)] <- 1
donner$Age <- NULL
donner$Status <- as.numeric(donner$Status)
donner$Sex[donner$Sex == 2] <- 0
logregmodel <- train(Status ~ ., data = donner, method = "logreg", trControl = ctrl)

Answer 2

我个人从来没有使用过 "logreg" 方法。似乎有些台词也没用。这是我使用 "glm" 作为方法的建议。

## Data
donner <- read.delim("http://web.as.uky.edu/statistics/users/pbreheny/760/data/donner.txt")

set.seed(1234)
library(caret)

donner$Age <- as.numeric(donner$Age)
donner$Status <- as.factor(donner$Status)
donner$Sex <- as.numeric(donner$Sex)-1 

splitIndex <- createDataPartition(donner$Status, p = .80, list = FALSE, times = 1)
trainDF <- donner[splitIndex,]
testDF <- donner[-splitIndex,]

ctrl <- trainControl(method = "cv", number = 3)
logregmodel <- train(Status ~ ., data = trainDF, method = "glm", family='binomial', trControl = ctrl)

summary(logregmodel)

Train function from R caret package error: "Something is wrong; all the Accuracy metric values are missing"

Train function from R caret package error: "Something is wrong; all the Accuracy metric values are missing"

r

r-caret