Details

    • Type: New Feature New Feature
    • Status: Closed
    • Priority: Major Major
    • Resolution: Fixed
    • Affects Version/s: 0.6
    • Fix Version/s: 0.7
    • Component/s: None
    • Labels:
      None

      Description

      It seems that a simple solution should exist to integrate PCA mean subtraction into SSVD algorithm without making it a pre-requisite step and also avoiding densifying the big input.

      Several approaches were suggested:

      1) subtract mean off B
      2) propagate mean vector deeper into algorithm algebraically where the data is already collapsed to smaller matrices
      3) --?

      It needs some math done first . I'll take a stab at 1 and 2 but thoughts and math are welcome.

      1. ssvd.m
        2 kB
        Raphael Cendrillon
      2. ssvd-tests.R
        0.9 kB
        Dmitriy Lyubimov
      3. ssvd.R
        2 kB
        Dmitriy Lyubimov
      4. MAHOUT-817.patch
        120 kB
        Dmitriy Lyubimov
      5. MAHOUT-817.patch
        120 kB
        Dmitriy Lyubimov
      6. MAHOUT-817.patch
        120 kB
        Dmitriy Lyubimov
      7. MAHOUT-817-RC1.patch
        140 kB
        Dmitriy Lyubimov
      8. SSVD-PCA options.pdf
        369 kB
        Dmitriy Lyubimov
      9. SSVD-CLI.pdf
        406 kB
        Dmitriy Lyubimov

        Activity

        No work has yet been logged on this issue.

          People

          • Assignee:
            Dmitriy Lyubimov
            Reporter:
            Dmitriy Lyubimov
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            Dates

            • Created:
              Updated:
              Resolved:

              Development