Hi, I tried to implement a test case in rapid miner.

nn_here

Hi,

I tried to  implement a test case in rapid miner.

1.Loaded the training data,since it's a regression model, tried  with linear regression ..

2.After preprocessing the data and removing unnecessary column values, and applying the model and performance it has produced a result of decent accuracy.

3Now wanted to apply this model onto the testing data and check the performance and related attributes.

Kindly refer the attached doc containing the flow of operators used for both training and testing dataset for reaching the target values.

 I have retrieved train and test data again and then gave used cross validation and applied the model

Can you please tell me if there is any way where the apply model only can be saved somewhere and then invoke it by giving the input as test data only ,without considering the training data. i have applied the entire operators used in the training data to testing data also which i feel is redundant .

Kindly help me in clarifying the same.
Thanks in advance.

CKönig

As a general rule, you should be applying the same preprocessing steps on both the training dataset and the testing dataset. This can make a huge difference, e.g. if you normalize the training dataset and the model expects values around 0, and then you feed it huge unnormalized numbers. It usually makes sense to put the preprocessing steps in a separate process that you can drag and drop into the training and scoring process. This also makes maintaining them much easier, since you only have to make changes in one place.