Comparison three methods of clustering: k-means, spectral clustering and hierarchical clustering
Comparison of three kind of the clustering and find cost function and loss function and calculate them. Error rate of the clustering methods and how to calculate the error percentage always be one on the important factor for evaluating the clustering methods, so this paper introduce one way to calcu...
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| Main Author | |
|---|---|
| Format | Journal Article |
| Language | English |
| Published |
19.12.2013
|
| Subjects | |
| Online Access | Get full text |
| DOI | 10.48550/arxiv.1312.6117 |
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| Abstract | Comparison of three kind of the clustering and find cost function and loss
function and calculate them. Error rate of the clustering methods and how to
calculate the error percentage always be one on the important factor for
evaluating the clustering methods, so this paper introduce one way to calculate
the error rate of clustering methods. Clustering algorithms can be divided into
several categories including partitioning clustering algorithms, hierarchical
algorithms and density based algorithms. Generally speaking we should compare
clustering algorithms by Scalability, Ability to work with different attribute,
Clusters formed by conventional, Having minimal knowledge of the computer to
recognize the input parameters, Classes for dealing with noise and extra
deposition that same error rate for clustering a new data, Thus, there is no
effect on the input data, different dimensions of high levels, K-means is one
of the simplest approach to clustering that clustering is an unsupervised
problem. |
|---|---|
| AbstractList | Comparison of three kind of the clustering and find cost function and loss
function and calculate them. Error rate of the clustering methods and how to
calculate the error percentage always be one on the important factor for
evaluating the clustering methods, so this paper introduce one way to calculate
the error rate of clustering methods. Clustering algorithms can be divided into
several categories including partitioning clustering algorithms, hierarchical
algorithms and density based algorithms. Generally speaking we should compare
clustering algorithms by Scalability, Ability to work with different attribute,
Clusters formed by conventional, Having minimal knowledge of the computer to
recognize the input parameters, Classes for dealing with noise and extra
deposition that same error rate for clustering a new data, Thus, there is no
effect on the input data, different dimensions of high levels, K-means is one
of the simplest approach to clustering that clustering is an unsupervised
problem. |
| Author | Kowsari, Kamran |
| Author_xml | – sequence: 1 givenname: Kamran surname: Kowsari fullname: Kowsari, Kamran |
| BackLink | https://doi.org/10.48550/arXiv.1312.6117$$DView paper in arXiv |
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| Snippet | Comparison of three kind of the clustering and find cost function and loss
function and calculate them. Error rate of the clustering methods and how to... |
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| Title | Comparison three methods of clustering: k-means, spectral clustering and hierarchical clustering |
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