根据随机森林对象预测响应填充数据

Question

Using randomForest , I get an RF object.
Eg forest <- randomForest(as.formula(generic),data=train, mtry=2) )

Using predict I can predict the response on a test dataset.
The response is either A,B or C.

prediction <- predict(forest, newdata=test, type='class')
mytable <- table(test$class_w,prediction)
sum(mytable[row(mytable) != col(mytable)]) / sum(mytable)#show error

Calling the forest object I get the confusion matrix:

     A     B    C     class.error
A   498    79   170   0.3333333
B   115    353  237   0.4992908
C   96     99   967   0.1678141

Eg test dataset :

id |class_w| valueA | valueB |
1  |  C    |  0.254 |  0.334 |
2  |  A    |  0.654 |  0.334 |
3  |  A    |  0.554 |  0.314 |
4  |  B    |  0.454 |  0.224 |
5  |  C    |  0.354 |  0.332 |
6  |  C    |  0.264 |  0.114 |
7  |  C    |  0.264 |  0.664 |

I would like to know if I can create a new dataset with 2 columns the id of the previous dataset and the predicted response (the RF gave). Eg

row id of test dataset  |  predicted response
1                       |  A  #failed
2                       |  B  #failed
3                       |  B  #failed
4                       |  B  #TRUE!

Thanks in advance for your help.

Answer 1

I think you may simply be looking to create a new data frame:

data.frame(id = test$id,response = prediction)

That assumes that id is in fact a column in test , rather than the row names. If they are rownames, then you'd want to do:

data.frame(id = rownames(id),response = prediction)

Answer 2

An another way to do that would be to just write something like this:

yourNewDataSet$someNewColumnCreated= Predict(forest,yourNewDataSet,type="class")

This should give you a new column in your new dataset named 'someNewColumnCreated'

that will contain all the prediction of your model when applied to this new data set.