The Random-Cluster Model contains accounts of the subcritical and supercritical phases, together with clear statements of important open problems. The book includes treatment of the first-order (discontinuous) phase transition.
... Clustering In section Sect . 5.4 , HMM clustering and JClustering gave lower perplexities than frequency and random clustering when using the same number of bits for encoding the language model . To test how these models perform at ...
... randomized through randomly sampling training sentences , randomly selecting node - split questions , as well as randomly initializing data partition at each node, using 142 Y. Zhao et al . 5.6 Ensemble Learning Techniques for Language ...
... cluster can take. Inspecting the Clusters Now that we have generated our clusters, we can inspect each cluster manually and explore the assigned documents to get an understanding of its content. For example, let us take a few random ...
... clustering coeffi- cient simultaneously. Hyperbolic random graphs. Recently, a very promising model was introduced by Papadopoulos, Krioukov, Bogu ̃ná and Vahdat [18]. The authors demonstrated impressively that complex scale-free ...
... clusterings Erdős - Rényi Model : a random graph model F - measure : The harmonic mean between precision P and recall R Leipzig Corpora Collection : a collection of plain text corpora of standard- ized size for a large number of languages ...
... clustering and the groundtruth clustering. A related problem that has been studied in the literature [11] is planted clustering. In this model, the observation h is given by random noise applied to the ground truth clustering τ. Solving ...
... model , see e.g. , recent works in [ 6,10 ] . There exist a few sublinear - time algorithms for the k - median problem , that is algo- rithms with the running time of o ( n2 ) ( if we consider an ... Clustering Via Random Sampling 397.
... random seed. These models were then used for majority voting on the test set to derive final predictions. The same ... language model with an additional linear sequence classification layer rather than the 'bert-large-uncased ...