大型稀疏矩阵的奇异值分解的Java实现
我只是想知道是否有人知道大型稀疏矩阵的奇异值分解（SVD）的java实现？我需要这个实现来进行潜在语义分析（LSA）。
我尝试了 UJMP 和 JAMA 的软件包，但是当行数 >= 1000 和列数 >= 500 时，它们就会窒息。如果有人能指出我的伪代码或其他东西，我将不胜感激。
I'm just wondering if anyone out there knows of a java implementation of singular value decomposition (SVD) for large sparse matrices? I need this implementation for latent semantic analysis (LSA).
I tried the packages from UJMP and JAMA but they choke when the number of row >= 1000 and col >= 500. If anyone can point me to psuedocode or something out there, that would be greatly appreciated.
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Wikipedia 上有一个 Java 数值库列表。 NIST 库相当不错，但不幸的是不处理稀疏矩阵。我对其他包不太熟悉。您可以查看 Colt；它的质量也相当高，并且确实可以处理某些操作的稀疏矩阵；我不知道 SVD，尽管我想它是这样的。我还听说 UJMP 也值得一看。
编辑：很抱歉听到 UJMP 无法处理您的问题。我听说值得一看。
There's a list of Java numerical libraries at Wikipedia. The NIST library, which is quite good, unfortunately does not deal with sparse matrices. I'm not too familiar with the other packages. You might take a look at Colt; it's also quite high quality and does handle sparse matrices for some operations; I don't know about SVD, although I imagine it does. I've also heard that UJMP is also worth a look.
EDIT: Sorry to hear that UJMP doesn't handle your problem. I had heard that it was worth a look.