Hiroaki Kubota created MAHOUT-1066:
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Summary: How to generate sparsed Vectors from the specified
dictionary.
Key: MAHOUT-1066
URL: https://issues.apache.org/jira/browse/MAHOUT-1066
Project: Mahout
Issue Type: Question
Components: Clustering
Affects Versions: 0.7
Reporter: Hiroaki Kubota
I'd like to do clustering our natural language data.
The first, I used the 'seq2sparse' command to vectorize our data.
I got sparsed vectors and a dictionary.
And we could do k-means and got suitable clusters.
It was OK.
The next, I'd like to add some data to previous calculated clusters.
So I want to get additional vectors from new additional data based on previous
dictionary.
Probably I think,
It is impossible to get really accurate vectors by using only additional data.
However,I'd like to reduce processing time so It's OK if I get the vector that
is useful for decision tree.
Please give me advice !
Regard,
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