Advantages of Consensus Clustering
- Provides for a method to represent the consensus across multiple runs of a clustering algorithm, to determine the number of clusters in the data, and to assess the stability of the discovered clusters.
- The method can also be used to represent the consensus over multiple runs of a clustering algorithm with random restart (such as K-means, model-based Bayesian clustering, SOM, etc.), so as to account for * its sensitivity to the initial conditions.
- It also provides for a visualization tool to inspect cluster number, membership, and boundaries.
- We will be able to extract lot of features / attributes from multiples runs of different clustering algorithms on the data. These features can give us valuable information in doing a final consensus clustering.
Read more about this topic: Consensus Clustering
Famous quotes containing the words advantages of, advantages and/or consensus:
“In 1845 he built himself a small framed house on the shores of Walden Pond, and lived there two years alone, a life of labor and study. This action was quite native and fit for him. No one who knew him would tax him with affectation. He was more unlike his neighbors in his thought than in his action. As soon as he had exhausted himself that advantages of his solitude, he abandoned it.”
—Ralph Waldo Emerson (1803–1882)
“Men hear gladly of the power of blood or race. Every body likes to know that his advantages cannot be attributed to air, soil, sea, or to local wealth, as mines and quarries, nor to laws and traditions, nor to fortune, but to superior brain, as it makes the praise more personal to him.”
—Ralph Waldo Emerson (1803–1882)
“Nothing defines the quality of life in a community more clearly than people who regard themselves, or whom the consensus chooses to regard, as mentally unwell.”
—Renata Adler (b. 1938)