本文介绍了大术语文档矩阵/simple_triplet_matrix 的行总和 ??{tm 包}的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
所以我有一个非常大的术语文档矩阵:
So I have a very large term-document matrix:
> class(ph.DTM)
[1] "TermDocumentMatrix" "simple_triplet_matrix"
> ph.DTM
A term-document matrix (109996 terms, 262811 documents)
Non-/sparse entries: 3705693/28904453063
Sparsity : 100%
Maximal term length: 191
Weighting : term frequency (tf)
如何获得每个术语的 rowSum(频率)?我试过了:
How do I get the rowSum (frequency) of each term? I tried:
> apply(ph.DTM, 1, sum)
Error in vector(typeof(x$v), nr * nc) : vector size cannot be NA
In addition: Warning message:
In nr * nc : NAs produced by integer overflow
显然,我知道removeSparseTerms
:
ph.DTM2 <- removeSparseTerms(ph.DTM, 0.99999)
缩小尺寸:
> ph.DTM2
A term-document matrix (28842 terms, 262811 documents)
Non-/sparse entries: 3612620/7576382242
Sparsity : 100%
Maximal term length: 24
Weighting : term frequency (tf)
但我仍然无法对其应用任何与矩阵相关的函数:
But I still cannot apply any matrix-related functions to it:
> as.matrix(ph.DTM2)
Error in vector(typeof(x$v), nr * nc) : vector size cannot be NA
In addition: Warning message:
In nr * nc : NAs produced by integer overflow
我怎样才能在这个对象上得到一个简单的行总和??谢谢!!
推荐答案
好吧,经过更多的 Google 搜索后,我遇到了 slam
包,它可以:
OK, after some more Google'ing, I came across the slam
package, which enables:
ph.DTM3 <- rollup(ph.DTM, 2, na.rm=TRUE, FUN = sum)
哪个有效.
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