Hi,It is a text format in which each line represents a labeled sparse feature
vector using the following format:label index1:value1 index2:value2 ...This was
the confusing part in the documentation:
"where the indices are one-based and in ascending order. After loading, the
feature indices are converted to zero-based."
Let us say that I have 40 features so I create an index file like this:
Feature, index number:F1 1F2 2F3 3...F4 40
I then create my feature vectors and in the libsvm format something like:1 10:1
20:0 8:1 4:0 24:11 1:1 40:0 2:1 8:0 9:1 23:10 23:1 18:0 13:1.....
I run regression and get back models.weights which are 40 weights.Say I get
0.110.34450.00005...
In that case does the first weight (0.11) correspond to index 1/ F1 or does or
correspond to index 2/F2? Since Input is 1-based and o/p is 0-based. Or is
0-based indexing is only for internal representation and what you get back at
the end of regression is essentially 1-based indexed like your input so 0.11
maps onto from F1and so on?
> Date: Mon, 22 Dec 2014 16:31:57 -0800
> Subject: Re: Interpreting MLLib's linear regression o/p
> From: men...@gmail.com
> To: ssti...@live.com
> CC: user@spark.apache.org
>
> Did you check the indices in the LIBSVM data and the master file? Do
> they match? -Xiangrui
>
> On Sat, Dec 20, 2014 at 8:13 AM, Sameer Tilak <ssti...@live.com> wrote:
> > Hi All,
> > I use LIBSVM format to specify my input feature vector, which used 1-based
> > index. When I run regression the o/p is 0-indexed based. I have a master
> > lookup file that maps back these indices to what they stand or. However, I
> > need to add offset of 2 and not 1 to the regression outcome during the
> > mapping. So for example to map the index of 800 from the regression output
> > file, I look for 802 in my master lookup file and then things make sense. I
> > can understand adding offset of 1, but not sure why adding offset 2 is
> > working fine. Have others seem something like this as well?
> >
>
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