cancer <- read.csv('breast-cancer-wisconsin.data', header = FALSE, na.strings="?")
cancer <- cancer[complete.cases(cancer),]
names(cancer)[11] <- "class"
cancer[, 11] <- factor(cancer[, 11], labels = c("benign", "malignant"))
library(gbm)
首先,我使用 complete.cases 删除“NA”值,并将第十一列“类”作为因子。我想使用“类”作为响应变量和其他列,除了第一个,作为预测变量。
在我第一次尝试时,我输入了:
boost.cancer <- gbm(class ~ .-V1, data = cancer, distribution = "bernoulli")
Error in gbm.fit(x, y, offset = offset, distribution = distribution, w = w, :
Bernoulli requires the response to be in {0,1}
然后,我使用类的对比而不是类。
boost.cancer <- gbm(contrasts(class) ~ .-V1, distribution = "bernoulli", data = cancer)
Error in model.frame.default(formula = contrasts(class) ~ . - V1, data = cancer, :
variable lengths differ (found for 'V1')
我该如何纠正这些错误?我确定我的方法有问题。