Question

我在R中使用支持向量机（SVM，包e1071）来构建分类模型和样本外预测7因子类。

问题是，当使用预测函数时，我获得了一个比验证集中的行数大得多的数组。请参阅下面的代码和结果。

关于出了什么问题的任何建议？我是否会错过 - 解释SVM包中的预测函数？

install.packages("e1071","caret")
library(e1071)
library(caret)

data <- data.frame(replicate(10,sample(0:6,1000,rep=TRUE)))

trainIndex <- createDataPartition(data[,1], p = 0.8,
                                  list = FALSE,
                                  times = 1)

trainset <- data[trainIndex,2:10]
validationset <- data[-trainIndex,2:10]

trainlabel <- data[trainIndex,1]
validationlabel <- data[-trainIndex,1]

svmModel <- svm(x = trainset, 
                y = trainlabel, 
                type = "C-classification", 
                kernel = "radial")

# Predict
svmPred <- predict(svmModel, x = validationset)

length(svmPred)
# 800, expected 200 since validationset has nrow = 200.

Answer 1

这是因为预测中不存在x

尝试：

val lines = ssc.fileStream[LongWritable, Text, TextInputFormat](
                  "/path/to/file", (file: Path) => 
                     FilenameUtils.getExtension(file.toString).equalsIgnoreCase("txt"))
               .map { case (_, text) => text.toString.split(" "))}

svm {e1071}预测会产生比预期更大的预测值数组

1 个答案: