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Assigning a new document to a cluster based on keywords extracted and tf-idf

You can use K-Nearest Neighbours classification using direct document vectors (if this is a better representation then I do not see an advantage in using tf-idf keywords) and using the cluster label (...
xabash's user avatar
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1 vote

Calculating weighted cosine similarity between vectors of words

Cosine similarity is not the best option because the data is not a vector. Better options could be Kullback–Leibler divergence or Hellinger distance. Both algorithms quantify the similarity between ...
Brian Spiering's user avatar
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Grouping similar classes to improve accuracy, whilst maximising the number of classes

To me it sounds like there are two different requirements for the aggregation. The overall task is to aggregate related classes, in a manner that improves accuracy. Breaking this down into two simpler ...
MuhammedYunus's user avatar
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Best metric to assess similarity between flight trajectories features

I think a variational autoencoder (VAE) with a 1D convolutional encoding stage might work. The 1D convolutional encoding stage would be able to encode trajectory data that is long, multivariate, and ...
MuhammedYunus's user avatar

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