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https://issues.apache.org/jira/browse/MAHOUT-550?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12935641#action_12935641
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Lance Norskog commented on MAHOUT-550:
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The use case that inspired gaussian01 is 100-300 dimensional matrices. The
matrices themselves were set from Random.linear(), meaning that distances
between the points were normal, but clamped. (linear + linear 600 times gives a
normal distribution. Clamped.)
The formula for this is clamp(low, high, (gaussian * factor) + 0.5)). Matrix
and Vector have everything but clamp(low, high). UnaryFunction would also work.
Hell, UnaryFunction might even be faster than all of these calls in a row.
> Add RandomVector and RandomMatrix
> ---------------------------------
>
> Key: MAHOUT-550
> URL: https://issues.apache.org/jira/browse/MAHOUT-550
> Project: Mahout
> Issue Type: New Feature
> Components: Math
> Reporter: Lance Norskog
> Fix For: 0.5
>
> Attachments: MAHOUT-550.patch, RandomMatrix.patch
>
>
> Add Vector and Matrix implementations that generate a unique and reproducible
> random number for each index.
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