The 0 vector is a trivial solution. Is the data big, such that it can't be computed on one machine? if so I assume this system is over-determined. You can use a decomposition to find a least-squares solution, but the SVD is overkill and in any event distributed decompositions don't exist in the project. You can solve it a linear regression as Mr Das says.
If it's small enough to fit locally you should just use a matrix library to solve Ax = b with the QR decomposition or something, with Breeze or Commons Math or octave or R. Lots of options if it's smallish. On Thu, Oct 23, 2014 at 12:15 AM, Martin Enzinger <martin.enzin...@gmail.com> wrote: > Hi, > > I'm wondering how to use Mllib for solving equation systems following this > pattern > > 2*x1 + x2 + 3*x3 + .... + xn = 0 > x1 + 0*x2 + 3*x3 + .... + xn = 0 > .......... > .......... > 0*x1 + x2 + 0*x3 + .... + xn = 0 > > I definitely still have some reading to do to really understand the direct > solving techniques, but at the current state of "knowledge" SVD could help > me with this right? > > Can you point me to an example or a tutorial? > > best regards --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
