使用SVM模型进行预测时，R返回系数(0) [英] R returns factor(0) when predicting with a SVM model

问题描述

我的问题与此线程完全相同.但是，由于这似乎还没有令人满意的答案，因此我认为再次询问可复制的代码仍然是适当的.

My question is quite the same with this thread, however, since that seems not to have an satisfying answer yet, I think it is still appropriate to ask again along with reproducible codes.

training <- read.csv("https://d396qusza40orc.cloudfront.net/predmachlearn/pml-training.csv")[,-1]
testing <- read.csv("https://d396qusza40orc.cloudfront.net/predmachlearn/pml-testing.csv")[,-1]
# Importing data

library(e1071)
# Load the required package for SVM

svm_model <- svm(classe ~ pitch_arm + pitch_forearm + pitch_dumbbell + pitch_belt +
  roll_arm + roll_forearm + roll_dumbbell + roll_belt +
  yaw_arm + yaw_forearm + yaw_dumbbell + yaw_belt,
  data = training, scale = FALSE, cross = 10)
# Perform SVM analysis with default gamma and cost, and do 10-fold cross validation

predict(svm_model, testing)
# R returns factor(0) here

我已经检查了测试数据帧是否具有所有需要的列，并且那些必需的列中不存在NA.请给我一些想法继续.谢谢！

I have checked that testing data frame has all columns needed, and no NA exists in those required columns. Please give me some ideas to carry on. Thanks!

推荐答案

这似乎是e1071预告.svm函数中一个古怪的结果.虽然您的测试数据没有模型中变量的缺失值.每个点都有缺失值.

This seems to be the result of a quirk in the e1071 predict.svm function. While your test data has no missing values for the variables in your model. Every point has missing values.

complete.cases(testing)
 [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
[14] FALSE FALSE FALSE FALSE FALSE FALSE FALSE

您可以通过消除不需要的变量来解决此问题.

You can work around this problem by eliminating the unneeded variables.

ModelVars = which(names(training) %in% 
    c("pitch_arm", "pitch_forearm", "pitch_dumbbell", "pitch_belt",
    "roll_arm", "roll_forearm", "roll_dumbbell", "roll_belt", 
    "yaw_arm", "yaw_forearm", "yaw_dumbbell", "yaw_belt"))
test2  = testing[, ModelVars]

predict(svm_model, test2)
 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 
 A  A  B  A  A  A  D  B  A  A  A  C  A  A  A  A  A  A  A  A 
Levels: A B C D E

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