Adds the given data items.
Adds the given data items.
Clears all data items.
Clears all data items.
Clears the state of all data items (but does not remove them).
Clears the state of all data items (but does not remove them).
Clears the model state (re-initializes).
Clears the model state (re-initializes).
Model companion used by this modeler.
Model companion used by this modeler.
Sharded view of data.
Sharded view of data. ListBuffer's toList does not make a copy.
Description of the model being trained.
Description of the model being trained.
Returns all data items.
Returns all data items.
Returns the number of data items available.
Returns the number of data items available.
Returns the state of all data items.
Returns the state of all data items.
Returns a function of the given data states.
Returns a function of the given data states.
Gets the current model state.
Gets the current model state.
Clears all documents and begins using the given model.
Clears all documents and begins using the given model.
Does one iteration of learning.
Does one iteration of learning.
The shards that will contain the data.
Returns the current model, if one has been initialized.
Returns the current model, if one has been initialized.
Each model is created independently.
Train the model on the given data.
Train the model on the given data.
Uses the given data state.
Uses the given data state.
Uses the given ModelState in the current model.
Uses the given ModelState in the current model.
Runs data parallel models as multiple threads on a single machine.