Can we use our own data set to train the models and predict our own test set? #14
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You can, just make sure the input format remains the same.
…On Wed, Oct 17, 2018 at 7:24 AM xinxu1018 ***@***.***> wrote:
Can we use our own data set to train the models and predict our own test
set?
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@Sshanu Thanks so much for your quick response! Please allow me to ask one more question. All the best! |
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I first extracted words and stored it in a list named as vocab, then
extracted word embedding and stored it in a numpy array.
If 2nd word in vocab is "the", the 2nd row in numpy array will have word
embedding corresponding to "the".
I then saved both vocab and word embedding numpy array using pickle.
So, you can create a similar array and vocab, or you can change the code to
load embeddings.
…On Wed, Oct 17, 2018 at 9:14 PM xinxu1018 ***@***.***> wrote:
@Sshanu <https://github.com/Sshanu> Thanks so much for your quick
response! Please allow me to ask one more question.
Since I am using word embeddings trained over my specific corpus instead
of your given Glove embeddings, how can I get my embeddings in the same
format with the Glove embedding file you provided in the data folder and
use it in your designed LSTM model?
All the best!
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@xinxu1018 That is so informative! Thanks a lot! |
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@Sshanu It works! Thanks a lot! Can I ask a follow-up question again? Many thanks! |
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You can try this approach but its shortcoming is that you don't have word
embedding for the multi-word term. Create a dependency tree, then choose
entity from the two word which is below another one in the tree, then the
information regarding the other word will be computed from the lstm -tree,
and instead of only using features of lca, entity1, and entity2 from the
lstm-tree for relation classification, also use the features of the other
word from the lstm-tree.
I did not work on Relation Classification or any related field after this
project, this project was my first in NLP, that's why I have very less
knowledge in this relation classification or extraction.
…On Thu, Oct 18, 2018 at 12:57 AM xinxu1018 ***@***.***> wrote:
@Sshanu <https://github.com/Sshanu> It works! Thanks a lot! Can I ask a
follow-up question again?
If I wanna classify relations between multi-word terms (in your case it is
one-word term pairs), how can I preprocess the sentences before I go to the
step of dependency path extraction? Do you have any suggestions? One way I
am considering is to connect every word within a multi-word term using
underscores (like, "system configuration" to "system_configuration" ) and
then treat them as a one-word term. Then follow your designed procedures.
Not sure if it will work. Do you have any ideas?
Many thanks!
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@Sshanu Thanks a lot! Hope you everything goes very well! |
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@Sshanu Could you please provide your word_embd_wiki file? I cannot find the embedding file in your given data folder. Thanks for you help! Best, |
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My google drive is full, please share a folder with me, where I will upload
the word_embed file.
…On Thu, Oct 18, 2018 at 9:03 PM xinxu1018 ***@***.***> wrote:
@Sshanu <https://github.com/Sshanu> Could you please provide your
word_embd_wiki file? I cannot find the embedding file in your given data
folder. Thanks for you help!
Best,
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@Sshanu How can I share a folder with you? What's your address? Sorry, I am new here! |
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@Sshanu Hi Sshanu, I just shared a google drive folder to the email you provided in your Github profile. Not sure am I doing right! Many thanks! |
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Oh, please share it with [email protected]
…On Thu, Oct 18, 2018 at 9:43 PM xinxu1018 ***@***.***> wrote:
@Sshanu <https://github.com/Sshanu> Hi Sshanu, I just shared a google
drive folder to the email you provided in your Github profile. Not sure am
I doing right! Many thanks!
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@Sshanu I have shared to your gmail. Please check and many thanks! |
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@Sshanu Hi Sshanu, got your shared file! You helped me a lot! I am just wondering do you have the original code that was used to separate embedding file into vocab and word_embedding arrays? Then I can generate my own trained embeddings into the format aligned with your designed method. Could you please share me the code? Thanks again! |
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I don't have the file, if you are having a problem in generating the exact
file, then simply try storing the embeddings in numpy array and vocabulary
in a list, my code will work afterward.
…On Fri, Oct 19, 2018 at 10:17 AM xinxu1018 ***@***.***> wrote:
@Sshanu <https://github.com/Sshanu> Hi Sshanu, got your shared file! You
helped me a lot! I am just wondering do you have the original code that was
used to separate embedding file into vocab and word_embedding arrays? Then
I can generate my own trained embeddings into the format aligned with your
designed method. Could you please share me the code? Thanks again!
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Can we use our own data set to train the models and predict our own test set?
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