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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.
Is this possible ?
Basically something like:
"rescore": {
"window_size": 1000,
"query": {
"rescore_query": {
"sltr": {
"params": {
"keywords": "rambo"
},
"model": "my_model",
"active_features": [0.1, 0.2, 0.4, 0.2, ... etc]
}
}
}
}
}
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