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Hi, so I have a desire to use this plugin in an unconventional way. I want to use a pre-trained xgboost model and provide a one hot encoded DenseFeatureVector as a query param which will be used in rescoring all my results, rather than use the FeatureSet framework paradigm.
I believe a model requires a featureset to be created, so you'd need at least a dummy featureset like you said. Since a model's features already accept params, you'd just be calling sltr with active_features under the params key at the same level at keywords
Hi, so I have a desire to use this plugin in an unconventional way. I want to use a pre-trained xgboost model and provide a one hot encoded DenseFeatureVector as a query param which will be used in rescoring all my results, rather than use the FeatureSet framework paradigm.
Is this possible ?
Basically something like:
}
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