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Write the cluster in dataset
microsoft.public.sqlserver.clustering microsoft.public.sqlserver.clustering
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#41
 
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RE: Write the cluster in dataset -
09-19-2008
, 05:32 PM
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What did your clustering processing do? What do you mean by writing the final clusters in a table'? Linchi "Paulo" wrote: Hi guys, Please, how can I write, after clustering process, the final clusters in a table? Best, -- Paulo Carvalho |
#42
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I'm running K-Means So I just want to create a field with the cluster group in the table that I applied the method... |
=========
K-means algorithm
From Wikipedia, the free encyclopedia
The k-means algorithm is an algorithm to cluster n objects based on
attributes into k partitions, k < n. It is similar to the
expectation-maximization algorithm for mixtures of Gaussians in that
they both attempt to find the centers of natural clusters in the data.
It assumes that the object attributes form a vector space. The
objective it tries to achieve is to minimize total intra-cluster
variance, or, the squared error function
==========
I hate to disappoint you but microsoft.public.sqlserver.clustering is
for the discussion of Microsoft SQL Server running on multiple
(clustered) Windows servers. The idea is when one server goes down,
another server in the cluster takes over the work.
Which is quite different from K-Means.
Roy Harvey
Beacon Falls, CT
#43
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I'm running K-Means So I just want to create a field with the cluster group in the table that I applied the method... |
=========
K-means algorithm
From Wikipedia, the free encyclopedia
The k-means algorithm is an algorithm to cluster n objects based on
attributes into k partitions, k < n. It is similar to the
expectation-maximization algorithm for mixtures of Gaussians in that
they both attempt to find the centers of natural clusters in the data.
It assumes that the object attributes form a vector space. The
objective it tries to achieve is to minimize total intra-cluster
variance, or, the squared error function
==========
I hate to disappoint you but microsoft.public.sqlserver.clustering is
for the discussion of Microsoft SQL Server running on multiple
(clustered) Windows servers. The idea is when one server goes down,
another server in the cluster takes over the work.
Which is quite different from K-Means.
Roy Harvey
Beacon Falls, CT
#44
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|
|
I'm running K-Means So I just want to create a field with the cluster group in the table that I applied the method... |
=========
K-means algorithm
From Wikipedia, the free encyclopedia
The k-means algorithm is an algorithm to cluster n objects based on
attributes into k partitions, k < n. It is similar to the
expectation-maximization algorithm for mixtures of Gaussians in that
they both attempt to find the centers of natural clusters in the data.
It assumes that the object attributes form a vector space. The
objective it tries to achieve is to minimize total intra-cluster
variance, or, the squared error function
==========
I hate to disappoint you but microsoft.public.sqlserver.clustering is
for the discussion of Microsoft SQL Server running on multiple
(clustered) Windows servers. The idea is when one server goes down,
another server in the cluster takes over the work.
Which is quite different from K-Means.
Roy Harvey
Beacon Falls, CT
#45
| |||
| |||
|
|
I'm running K-Means So I just want to create a field with the cluster group in the table that I applied the method... |
=========
K-means algorithm
From Wikipedia, the free encyclopedia
The k-means algorithm is an algorithm to cluster n objects based on
attributes into k partitions, k < n. It is similar to the
expectation-maximization algorithm for mixtures of Gaussians in that
they both attempt to find the centers of natural clusters in the data.
It assumes that the object attributes form a vector space. The
objective it tries to achieve is to minimize total intra-cluster
variance, or, the squared error function
==========
I hate to disappoint you but microsoft.public.sqlserver.clustering is
for the discussion of Microsoft SQL Server running on multiple
(clustered) Windows servers. The idea is when one server goes down,
another server in the cluster takes over the work.
Which is quite different from K-Means.
Roy Harvey
Beacon Falls, CT
#46
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|
|
I'm running K-Means So I just want to create a field with the cluster group in the table that I applied the method... |
=========
K-means algorithm
From Wikipedia, the free encyclopedia
The k-means algorithm is an algorithm to cluster n objects based on
attributes into k partitions, k < n. It is similar to the
expectation-maximization algorithm for mixtures of Gaussians in that
they both attempt to find the centers of natural clusters in the data.
It assumes that the object attributes form a vector space. The
objective it tries to achieve is to minimize total intra-cluster
variance, or, the squared error function
==========
I hate to disappoint you but microsoft.public.sqlserver.clustering is
for the discussion of Microsoft SQL Server running on multiple
(clustered) Windows servers. The idea is when one server goes down,
another server in the cluster takes over the work.
Which is quite different from K-Means.
Roy Harvey
Beacon Falls, CT
#47
| |||
| |||
|
|
I'm running K-Means So I just want to create a field with the cluster group in the table that I applied the method... |
=========
K-means algorithm
From Wikipedia, the free encyclopedia
The k-means algorithm is an algorithm to cluster n objects based on
attributes into k partitions, k < n. It is similar to the
expectation-maximization algorithm for mixtures of Gaussians in that
they both attempt to find the centers of natural clusters in the data.
It assumes that the object attributes form a vector space. The
objective it tries to achieve is to minimize total intra-cluster
variance, or, the squared error function
==========
I hate to disappoint you but microsoft.public.sqlserver.clustering is
for the discussion of Microsoft SQL Server running on multiple
(clustered) Windows servers. The idea is when one server goes down,
another server in the cluster takes over the work.
Which is quite different from K-Means.
Roy Harvey
Beacon Falls, CT
#48
| |||
| |||
|
|
I'm running K-Means So I just want to create a field with the cluster group in the table that I applied the method... |
=========
K-means algorithm
From Wikipedia, the free encyclopedia
The k-means algorithm is an algorithm to cluster n objects based on
attributes into k partitions, k < n. It is similar to the
expectation-maximization algorithm for mixtures of Gaussians in that
they both attempt to find the centers of natural clusters in the data.
It assumes that the object attributes form a vector space. The
objective it tries to achieve is to minimize total intra-cluster
variance, or, the squared error function
==========
I hate to disappoint you but microsoft.public.sqlserver.clustering is
for the discussion of Microsoft SQL Server running on multiple
(clustered) Windows servers. The idea is when one server goes down,
another server in the cluster takes over the work.
Which is quite different from K-Means.
Roy Harvey
Beacon Falls, CT
#49
| |||
| |||
|
|
I'm running K-Means So I just want to create a field with the cluster group in the table that I applied the method... |
=========
K-means algorithm
From Wikipedia, the free encyclopedia
The k-means algorithm is an algorithm to cluster n objects based on
attributes into k partitions, k < n. It is similar to the
expectation-maximization algorithm for mixtures of Gaussians in that
they both attempt to find the centers of natural clusters in the data.
It assumes that the object attributes form a vector space. The
objective it tries to achieve is to minimize total intra-cluster
variance, or, the squared error function
==========
I hate to disappoint you but microsoft.public.sqlserver.clustering is
for the discussion of Microsoft SQL Server running on multiple
(clustered) Windows servers. The idea is when one server goes down,
another server in the cluster takes over the work.
Which is quite different from K-Means.
Roy Harvey
Beacon Falls, CT
#50
| |||
| |||
|
|
I'm running K-Means So I just want to create a field with the cluster group in the table that I applied the method... |
=========
K-means algorithm
From Wikipedia, the free encyclopedia
The k-means algorithm is an algorithm to cluster n objects based on
attributes into k partitions, k < n. It is similar to the
expectation-maximization algorithm for mixtures of Gaussians in that
they both attempt to find the centers of natural clusters in the data.
It assumes that the object attributes form a vector space. The
objective it tries to achieve is to minimize total intra-cluster
variance, or, the squared error function
==========
I hate to disappoint you but microsoft.public.sqlserver.clustering is
for the discussion of Microsoft SQL Server running on multiple
(clustered) Windows servers. The idea is when one server goes down,
another server in the cluster takes over the work.
Which is quite different from K-Means.
Roy Harvey
Beacon Falls, CT
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