Closed
Description
Take another pass over the trainers and the model parameter types, and align them, because now we have:
LogisticRegressionMulticlassClassificationTrainer
but MulticlassLogisticRegressionModelParameters
.
I think following the same principles on the ModelParams might make them more relatable; so change MulticlassLogisticRegressionModelParameters
to LogisticRegressionMulticlassModelParameters
Activity
sfilipi commentedon Mar 13, 2019
@shauheen would this be a candidate for Project 13?
abgoswam commentedon Mar 14, 2019
In general, it seems there isn't a 1:1 mapping between trainer and model parameter types.
SdcaNonCalibratedBinaryClassificationTrainer
usesLinearBinaryModelParameters
SdcaCalibratedBinaryClassificationTrainer
usesCalibratedModelParametersBase
as type of the model parameter.However, there are some discrepancies that exists. Whenever possible we should align the trainer and model parameter types.
Listing some of the trainers where we can fix this :
abgoswam commentedon Mar 18, 2019
Update:
To keep consistency between Class names of Trainers and ModelParameters, we will not use the word "Classification" in either the Trainer class or the ModelParameter class
We feel its OK to drop the word "Classification" for 2 main reasons :
Here is a summary of the Trainer and ModelParameter class names
wschin commentedon Mar 18, 2019
For multi-class LR trainer and its model, we will different names in #2976. Looks like they don't need
multiclass
.We can NOT have LogisticRegressionMulticlass because LogisticRegression is binary classification only.