如何繪製R中的學習曲線？

Question

我想在我的應用程序中繪製一條學習曲線。

樣本曲線圖如下所示。

學習曲線是以下方差之間的曲線圖，

• X軸：樣本數（訓練集的大小）。
• Y軸：錯誤（RSS/J（THETA）/成本函數）

它有助於我們觀察模型是否具有高偏壓或高方差問題。

R中有沒有可以幫助獲得這個陰謀的軟件包？

Answer 1

您可以使用出色的Caret包進行這樣的繪圖。關於Customizing the tuning process的部分將會非常有幫助。

另外，你可以看看由Joseph Rickert編寫的關於R-Bloggers的博客文章。標題分別爲"Why Big Data? Learning Curves"和"Learning from Learning Curves"。

UPDATE
我只是做了這個問題Plot learning curves with caret package and R一個職位。我想我的回答對你更有用。爲了方便起見，我在這裏再次繪製了與R繪製學習曲線相同的答案。但是，我使用流行的caret包來訓練我的模型並獲得訓練和測試集的RMSE誤差。

# set seed for reproducibility 
set.seed(7) 

# randomize mtcars 
mtcars <- mtcars[sample(nrow(mtcars)),] 

# split iris data into training and test sets 
mtcarsIndex <- createDataPartition(mtcars$mpg, p = .625, list = F) 
mtcarsTrain <- mtcars[mtcarsIndex,] 
mtcarsTest <- mtcars[-mtcarsIndex,] 

# create empty data frame 
learnCurve <- data.frame(m = integer(21), 
        trainRMSE = integer(21), 
        cvRMSE = integer(21)) 

# test data response feature 
testY <- mtcarsTest$mpg 

# Run algorithms using 10-fold cross validation with 3 repeats 
trainControl <- trainControl(method="repeatedcv", number=10, repeats=3) 
metric <- "RMSE" 

# loop over training examples 
for (i in 3:21) { 
    learnCurve$m[i] <- i 

    # train learning algorithm with size i 
    fit.lm <- train(mpg~., data=mtcarsTrain[1:i,], method="lm", metric=metric, 
      preProc=c("center", "scale"), trControl=trainControl)   
    learnCurve$trainRMSE[i] <- fit.lm$results$RMSE 

    # use trained parameters to predict on test data 
    prediction <- predict(fit.lm, newdata = mtcarsTest[,-1]) 
    rmse <- postResample(prediction, testY) 
    learnCurve$cvRMSE[i] <- rmse[1] 
} 

pdf("LinearRegressionLearningCurve.pdf", width = 7, height = 7, pointsize=12) 

# plot learning curves of training set size vs. error measure 
# for training set and test set 
plot(log(learnCurve$trainRMSE),type = "o",col = "red", xlab = "Training set size", 
      ylab = "Error (RMSE)", main = "Linear Model Learning Curve") 
lines(log(learnCurve$cvRMSE), type = "o", col = "blue") 
legend('topright', c("Train error", "Test error"), lty = c(1,1), lwd = c(2.5, 2.5), 
     col = c("red", "blue")) 

dev.off() 

輸出情節如下圖所示：