SVM 基于最后一列的数据框答案

【问题标题】：SVM a dataframe based on the last columnSVM 基于最后一列的数据框
【发布时间】：2017-08-13 22:02:33
【问题描述】：

我一直在尝试根据最后一个类名来支持数据帧。

我有这个数据框

#FIll the data frame
df = read.table("https://archive.ics.uci.edu/ml/machine-learning-databases/car/car.data",
               sep=",",
               col.names=c("buying", "maint", "doors", "persons", "lug_boot", "safety", ""),
               fill=TRUE,
               strip.white=TRUE)

lastColName <- colnames(df)[ncol(df)]

...

model <- svm(lastColName~.,
             data = df,
             kernel="polynomial",
             degree = degree,
             type = "C-classification",
             cost = cost)

我收到的是 NULL 或 Error in model.frame.default(formula = str(lastColName) ~ ., data = df1, : invalid type (NULL) for variable 'str(lastColName)'。我知道NULL 在列没有名称时到达。我不明白另一个错误，因为它是最后一列名称..

有什么想法吗？

【问题讨论】：

标签： r dataframe svm

【解决方案1】：

当您尝试在公式中使用动态变量时，您必须使用as.formula。详情见?as.formula

以下代码可以正常工作：

library(e1071)
df_1 = read.table("https://archive.ics.uci.edu/ml/machine-learning-databases/car/car.data",
                sep=",",
                col.names=c("buying", "maint", "doors", "persons", "lug_boot", "safety", ""),
                fill=TRUE,
                strip.white=TRUE)

lastColName <- colnames(df_1)[ncol(df_1)]

model <- svm(as.formula(paste(lastColName, "~ .", sep = " ")),
             data = df_1,
             kernel="polynomial",
             degree = 3,
             type = "C-classification",
             cost = 1)
# to predict on the data remove the last column 
prediction <- predict(model, df_1[,-ncol(df_1)])

# The output
table(prediction)

# The output is:

prediction
acc  good unacc  vgood 
0     0    1728     0 

# Since this is a highly unbalanced classification the model is not doing a very good job

【讨论】：

哇，谢谢！但是，预测失败了，因为参数的长度不同。我使用了你的方法 => table(predict(model), as.formula(paste(lastColName, "~ .", sep = " ")), dnn=c("Prediction", "Actual"))
更新了从模型中预测的答案。