我试图弄清楚如何通过回归模型对数据集的另一部分进行测试，以使我开始感到困惑exportAsDoc() {
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，但我却错失了自己的错。
matrix当我这样预测时，我会收到此错误：
“ model.frame.default（条款，newdata，na.action = na.action， xlev = object $ xlevels）：因子状态具有新级别AP“
dupt：Report studentreport
答案 0 :(得分：0)
我重新输入了您发布的代码。由于在您的数据中找不到Enrolling列，因此在glm列中使用了GPATypeWeighted以便进行模型检查。未检测到预测错误。
library(leaps)
library(caret)
studentreport <- dget("https://drive.google.com/uc?authuser=0&id=1PHpkhPpEjIt-apCJpzvAKAlWZTPX7Evv&export=download")
studentreport <- data.frame(studentreport)
smp_size <- floor(0.75 * nrow(studentreport))
set.seed(123)
train_ind <- sample(seq_len(nrow(studentreport)), size = smp_size)
train <- studentreport[train_ind, ]
test <- studentreport[-train_ind, ]
fitreport <- glm(train)
Fitstart = glm(GPATypeWeighted ~ 1, data = train)
Report <- step(Fitstart, direction="forward", scope = formula(fitreport))
predict(Report, newdata = test, type ="response")
3 4 5 7 13 14 16 23 27 36
1.000000e+00 1.000000e+00 1.000000e+00 1.804986e-15 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00
37 43 44 56 57 60 62 64 66 69
1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 2.097525e-15
70 79 82 86 91 92 93 96 97 100
1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00
101 108 112 114 115 116 117 120 123 138
1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 2.199615e-15 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00
140 148 155 157 158 161 164 165 174 177
1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00
180 185 187 200 203 204 207 214 215 216
1.000000e+00 1.000000e+00 1.000000e+00 1.756027e-15 1.000000e+00 1.000000e+00 1.000000e+00 1.000000e+00 1.686952e-15 1.000000e+00
222 239 248
1.000000e+00 1.000000e+00 1.000000e+00