R 分层k-折叠情况下混淆矩阵和的计算
我是机器学习新手。我在我的数据集上应用了分层k倍。如何得到混淆矩阵的和 下面是我的代码R 分层k-折叠情况下混淆矩阵和的计算,r,machine-learning,confusion-matrix,R,Machine Learning,Confusion Matrix,我是机器学习新手。我在我的数据集上应用了分层k倍。如何得到混淆矩阵的和 下面是我的代码 library(MASS) cv_lda <- lapply(folds, function(x) { # start of function # in the next two lines we will separate the Training set into it's 10 pieces training_fold = ForwardPlayers[-x, ] # training
library(MASS)
cv_lda <- lapply(folds, function(x) { # start of function
# in the next two lines we will separate the Training set into it's 10 pieces
training_fold = ForwardPlayers[-x, ] # training fold = training set minus (-) it's sub test fold
test_fold = ForwardPlayers[x, ] # here we describe the test fold individually
# now apply (train) the classifer on the training_fold
classifier = lda(Rating ~ .,training_fold)
# next step in the loop, we calculate the predictions and cm and we equate the accuracy
# note we are training on training_fold and testing its accuracy on the test_fold
y_pred = predict(classifier, newdata = test_fold[-1])
cm = table(test_fold$Rating, y_pred$class)
#accuracy <- sum(diag(cm))/sum(cm)
return(cm)
})
库(MASS)
你试过这个吗
添加页边距()
->或任何边距子参数
作为论据