The Altair Community is migrating to a new platform to provide a better experience for you. In preparation for the migration, the Altair Community is on read-only mode from October 28 - November 6, 2024. Technical support via cases will continue to work as is. For any urgent requests from Students/Faculty members, please submit the form linked here
Missing input: ExampleSet regardless IOMultiplier
Legacy User
Member Posts: 0 
Newbie
HI,
I'm trying to compare two different learners with the T-Test operator. My model is pretty much
the same as sample 13_SignificanceTest. Even though I use the IOMultiplier operator to provide
the example set for both XValidation chains, RapidMiner issues an error telling me that an
example set is missing for the second learner. To reproduce, just run the mentioned example and
you get:
[Error] LinearRegression: LinearRegression: LinearRegression: Missing input: ExampleSet
[Error] There was 1 error.
So, is the error message redundant (since my example/the sample can be completely executed
and reasonable results are produced) or is there really something wrong?
Thx,
Benjamin
I'm trying to compare two different learners with the T-Test operator. My model is pretty much
the same as sample 13_SignificanceTest. Even though I use the IOMultiplier operator to provide
the example set for both XValidation chains, RapidMiner issues an error telling me that an
example set is missing for the second learner. To reproduce, just run the mentioned example and
you get:
[Error] LinearRegression: LinearRegression: LinearRegression: Missing input: ExampleSet
[Error] There was 1 error.
So, is the error message redundant (since my example/the sample can be completely executed
and reasonable results are produced) or is there really something wrong?
Thx,
Benjamin
0
Answers
the error appears, since the first [tt]XValidation[/tt] operator does not return an example set. Unfortunately, RM does not recognize that there is still one example set produced by the previous [tt]IOMultiplier[/tt]. That is already a known drawback of the RM process validation. The process validation does not consider the count of objects passed between operators, hence the error. Generally, you can ignore the error. An alternative which should not result in the error message would be to remove the [tt]IOMultiplier[/tt] and to set the parameter [tt]keep_example_set[/tt] of the first [tt]XValidation[/tt] operator to true.
Hope that helps,
Tobias