The state for this search node. @return the state

Returns all variables which are assigned to.

Gather statistics on the size of documents and create histograms for use in Dirichlet hyperparameter optimization.

Insert element <code>e</code> into the queue. @param e the element to insert

Returns true if <tt>filler</tt> is an exact match to one of the values of this field.

Returns an array of first-level keys.

Create a dummy label alphabet with <code>n</code> dimensions

Learn Dirichlet parameters using frequency histograms @param parameters A reference to the current values of the parameters, which will be updated in

Converts a FactorGraph into a plain graph where each Variable is a vertex, and two Variables are connected by an edge if they are arguments to the sam

Returns a <CODE>SparseVector</CODE> whose entries (taken from the union of those in the instances) are the expected values of those in the <CODE>Insta

Sample a multivariate normal from a precision matrix (ie inverse covariance matrix)

Return random integer from Poission with parameter lambda. The mean of this distribution is lambda. The variance is lambda.

Get the next reachable state. @return the state

Multiplies every entry in the potential by a constant such that all the entries sum to 1.

@param data Unlabeled data @return Returns a bitset of the size of the data, with the bit set if a constraint feature fires in that instance.

Prints a human-readable version of this vector, with features listed in ranked order. @param out Stream to write to

Write the internal representation of type-topic counts (count/topic pairs in descending order by count) to a file.

Pushes a new object onto the queue l @param l linked list queue of Matrix obj's @param toadd matrix to push onto queue

Constructs a square grid of a given size with random attractive potentials. Graphs are generated as follows: <p> We use a spin (i.e., {-1, 1}) repres

Constructs a square grid of a given size with random frustrated potentials. This means that some potentials will be attractive (want to make their n

Ranks all {@link Segment}s in this {@link InstanceList} by confidence estimate. @param ilist list of segmentation instances @param startTags

Resets the previous gradients and values that are used to approximate the Hessian. NOTE - If the {@link Optimizable} object is modified externally, th

Samples the continuous variables in this factor graph.