Help - Issue with Reject Inference Weights in SAS Visual Machine Learning

[teresacorzo]

I’m modelling with reject inference in SAS Visual Machine Learning, I have used the reject inference node with parcelling.

Previously, I’ve created models with reject inference in SAS Miner, where it assigned a weight to every registry in the dataset, assigning 1 to accepted and a given weight between 0 and 1 to the inferred data. However, in SAS Viya, the weights are all 1, in accepted and inferred.

I don’t need all the data in my modelling augmented data, but I don’t want to lose information by creating a random sample that mimics the weight assigned previously in Miner. The weight is given by the following equation:

I’ve tried assing this weight manually, assigning it as a Weight variable, but the node doesn’t read it, it includes all the observations for the rejected data with no calculated weight.

Train set Accepted:

Inferred:

I haven’t found enough information in internet to solve this problem.

Thanks!

[Sa_S]

Thank you for the post- we are responding in your TS case. Thanks, and have a great day!

[RoseCliver]

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@teresacorzo wrote:

I’m modelling with reject inference in SAS Visual Machine Learning, I have used the reject inference node with parcelling.

Previously, I’ve created models with reject inference in SAS Miner, where it assigned a weight to every registry in the dataset, assigning 1 to accepted and a given weight between 0 and 1 to the inferred data. However, in SAS Viya, the weights are all 1, in accepted and inferred.

I don’t need all the data in my modelling augmented data, but I don’t want to lose information by creating a random sample that mimics the weight assigned previously in Miner. The weight is given by the following equation:

I’ve tried assing this weight manually, assigning it as a Weight variable, but the node doesn’t read it, it includes all the observations for the rejected data with no calculated weight.

Train set Accepted:

Inferred:

I haven’t found enough information in internet to solve this problem.

Thanks!

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In SAS Visual Machine Learning, the Reject Inference Node does not automatically assign weights. Manually compute weights as in SAS Miner, then assign them using a custom "Weight" variable in the dataset. Ensure this variable is explicitly defined in the model settings to apply it during training.