Multiclass to two-class / binary classification problem
pal
Registered Posts: 3 ✭✭✭
I have a class-imbalance in data.
A - 59%
B - 33%
C and D each 4%
I want to use these as target classes and convert this into two-class problem and classify as A or not A (will have B, C, D)
I tried using " manually edit the mapping" on the target tab in model design. I assigned 1 to A and 0 to B,C,D.
However this does not work. It continues to give error as
Training failed
Read the logsFailed to train : <class 'ValueError'> : This is not a binary classification, found 4 classes
The only solution was to create a new table, add a column and populate it with 1 and 0 as required and then use it as target class. This required a new recipe and a new dataset.
Is there a way to avoid this? Any setting in the design page with allows me to map multiclass values of a target class to 0 and 1 so that I can proceed to two-class classification on the same table/dataset?
Many thanks
Pallavee
Operating system used: VM runing on Windows
Answers
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Emma Dataiker, Dataiku DSS Core Designer, Dataiku DSS ML Practitioner, Dataiku DSS Adv Designer, Registered Posts: 52 Dataiker
Hey @pal
,You can accomplish this type of data preparation for modelling from within the AutoML Lab which eliminates the need for an additional recipe/output dataset. Navigate to the Script Tab along the top bar and then use a 'Find and Replace' processor to map A = 1, and B,C,D = 0.
Screenshots attached.
Hope that helps,
Emma