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AutoML with imbalaced dataset for multiclass classification - how to creat WEIGHT COLUMN?

Hello Guys,
I am using autoML for training purposes, however my dataset is very imbalanced.
It is a multiclass task with 5 classes and I want to minimize this effect when training.
I have verified the documentation and it seems autoML support the creation of a new column with weights.

My doubts are: What is the range I am supposed to use? At this moment I am using 30, 40, 1.5 and 4. Can I use them? Also, for new dataset this column will not exist anymore, so how can the model understand that?

azure-machine-learning-studio-classic
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Hello @Mary-1005

I think you are talking about Azure Machine Learning Services not studio classic. The range depends on what your data set looks like. Here is a good blog talking about the range and I hope it helps you to understand this a little bit.

https://techcommunity.microsoft.com/t5/azure-ai/dealing-with-imbalanced-data-in-automl/ba-p/1625043


Regards,
Yutong

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Hello Yutong,

Yes, I am not talking abot the Studio Class.

IWhen I ran my first experiment, I let autoML work by itself and it only detected one class imbalanced, however my entire dataset with 5 classes is very imbalanced on others classes too.

I checked this link and there is no mention about the column weight I am asking here, like it is described:
'
A weight column: automated ML supports a column of weights as input, causing rows in the data to be weighted up or down, which can be used to make a class more or less "important".'

This is the situation I would like to clear. If I can input my dataset already with this column or not.

Length of each class:

A: 12730
B: 181733
C: 623848
D: 1056696
E: 18210


Thanks

0 Votes 0 ·

Hello Yutong,

I was wondering about configuration mentioned on this link, I am not supposed to use line of code here, I am not using Python to build anything, I just would like to import my data to Azure Machine Learning AutoML and now I am with more doubts if I am doing it right.

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