Lecture Notes
lec08.pdf
Description:
This resource discusses about Vector-based similarity measures, probabilistic similarity measures, beyond pairwise similarity, hierarchical clustering, Agglomerative clustering, clustering function, Single-Link clustering, Complete-Link clustering, K-Means algorithm, comparing clustering by set matching, distributional syntax, linear vs. hierarchical context, grammar induction, motivation, evaluation and baselines, structure search experiment, finding topology, HMM topology induction, PCFG induction, Chunk/Merge systems, and partially unsupervised learning.
Resource Type:
Lecture Notes
pdf
224 kB
lec08.pdf
Course Info
Instructors
Departments
As Taught In
Fall
2005
Level
Course Info
Instructors
Departments
As Taught In
Fall
2005
Level
Learning Resource Types
notes
Lecture Notes
assignment
Problem Sets