Well the 3 in this case is the size of the sparse vector. This equates to
the number of features, which for CountVectorizer (I assume that's what
you're using) is also vocab size (number of unique terms).
On Tue, 25 Apr 2017 at 04:06 Peyman Mohajerian wrote:
> setVocabSize
>
>
> On Mon, Apr 24,
setVocabSize
On Mon, Apr 24, 2017 at 5:36 PM, Zeming Yu wrote:
> Hi all,
>
> Beginner question:
>
> what does the 3 mean in the (3,[0,1,2],[1.0,1.0,1.0])?
>
> https://spark.apache.org/docs/2.1.0/ml-features.html
>
> id | texts | vector
> |-
Hi all,
Beginner question:
what does the 3 mean in the (3,[0,1,2],[1.0,1.0,1.0])?
https://spark.apache.org/docs/2.1.0/ml-features.html
id | texts | vector
|-|---
0 | Array("a", "b", "c")| (3,[0,1,2],[1.0,1.
