Generate ranked example set from word vector data
aruberutou
MemberPosts:23
Contributor I
Hello,
This is my first post here, so please pardon any n00bishness.
I have a simple problem, with a potentially simple solution, and I am hoping for some kind help.
For a given example, is there a way to rank word vectors (i.e., sort decreasing) and then generate a new example set with, say:
- row titles "Rank 1", "Rank 2", ... "Rank 10"
- attributes titles corresponding to each example ID
- attribute values corresponding to the word vector titles (original attributes)
I have been trying to use transpose, followed by loop attributes containing: 1) sort (%{loop_attribute}), followed by 2) a generate attribute that copies the ranked words to a new example set as described above. I am stuck, however, at the "generate new example set" part.
This is easy enough in Excel, using the large() function. However, I was hoping to implement in Rapidminer, so as to save some effort.
Apologies if this has already been asked, or if its not as straight-forward as my post assumes.
Thanks in advance,
This is my first post here, so please pardon any n00bishness.
I have a simple problem, with a potentially simple solution, and I am hoping for some kind help.
For a given example, is there a way to rank word vectors (i.e., sort decreasing) and then generate a new example set with, say:
- row titles "Rank 1", "Rank 2", ... "Rank 10"
- attributes titles corresponding to each example ID
- attribute values corresponding to the word vector titles (original attributes)
I have been trying to use transpose, followed by loop attributes containing: 1) sort (%{loop_attribute}), followed by 2) a generate attribute that copies the ranked words to a new example set as described above. I am stuck, however, at the "generate new example set" part.
This is easy enough in Excel, using the large() function. However, I was hoping to implement in Rapidminer, so as to save some effort.
Apologies if this has already been asked, or if its not as straight-forward as my post assumes.
Thanks in advance,
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