Comments (4)
TBH I wanted to use TF for something + I wanted to have embeddings, that can be used as input to another network.
As for the order, I used bag-of-words and in this approach order didn't matter at all.
from game2vec.
But the order does matter--if the list of the games is bigger than the window size then the games outside the window size aren't part of that data point. Unless you set your window size to be at least as long as the longest list of games.
from game2vec.
I use a dynamic window. Each user's game is grouped together in a set, so for each user, I have a set of games that is a window.
To create a batch, while I do not have the required amount of (input, output) pairs I do the following:
- Randomly select a game set
- Using the game set, depending on method (CBOW, Skipgram), generate training pairs.
from game2vec.
Using a dynamic window would introduce some bias, in terms of what games are more likely to be in smaller collections (the most popular games?) are going to be drawn more. Although I'm not positive what the exact effects of this bias would be in terms of the vectors generated.
What's the other network you want to feed these vectors into (and why not have the network generate its own vector representation as part of the training)?
from game2vec.
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from game2vec.