Creates a document from the given document parameters.
Creates a document from the given document parameters.
The number of terms in the model.
The number of terms in the model.
The parameters used to create this model.
The parameters used to create this model.
Resets to the default state.
Resets to the default state.
Gets the current state of this object.
Gets the current state of this object.
Sets the current state of this object.
Sets the current state of this object.
Assert invariants.
Assert invariants.
Where log messages go.
Where log messages go. Defaults to System.err.println.
Registers a function as a checker of invariants.
Registers a function as a checker of invariants.
The term index describing which terms are in the model.
The term index describing which terms are in the model.
Tokenizes the given input string using our stored tokenizer and term index, if available.
Tokenizes the given input string using our stored tokenizer and term index, if available. Otherwise, throws an IllegalArgumentException.
The tokenizer used to break input documents into terms.
The tokenizer used to break input documents into terms.
Implementation trait for topic models. Here, we define a topic model to be any model with topics defined to be distributions over words and per-document per-word distributions over topic (in either a training or inference set).