relevanceai.operations_new.cluster.batch.transform#
TransformBase
Module Contents#
- class relevanceai.operations_new.cluster.batch.transform.BatchClusterTransform(vector_fields: list, model: Any, model_kwargs: dict, *args, **kwargs)#
To write your own operation, you need to add: - name - transform
- partial_fit(self, documents: List, model_kwargs=None)#
Run partial fitting on a list of documents
- property name(self)#
abstractproperty for name
- property full_cluster_field(self)#
- transform(self, documents: List[Dict[str, Any]]) List[Dict[str, Any]]#
It takes a list of documents, and for each document, it runs the document through each of the models in the pipeline, and returns the updated documents.
- Parameters
documents (List[Dict[str, Any]]) – List[Dict[str, Any]]
- Return type
A list of dictionaries.
- predict_documents(self, documents, warm_start=False)#
If warm_start=True, copies the values from the previous fit. Only works for cluster models that use centroids. You should not have to use this parameter.