I have a dataset with me where the input is a sequence and output is just some labels. (No sequence in that) What is the best model to train that kind of dataset..?
I was using
seq2seq model. But the results were very low.
Then I used multi-label
svm with (1,7) ngrams. The result were better than seq2seq model. But not very good.
Can someone specify a better model..?
Input is actually a set of sequences.
When I was using
svm, the set was flatten and considered as a one sequence.
seq2seq model, the sequences were separated with a special symbol to identify that it is a different sequence.
Input sequence does not have a finite length. An example is given below.
Say I have
input vocab: AAA, BBB, CCC, DDD, EEE
output vocab: 111, 222, 333, 444
----Input Sequence----------------------Output (Order does not matter)-- AAA, BBB, DDD 111, 333 AAA, DDD, BBB 222, 333 DDD, BBB, AAA, CCC 111, 444, 222 BBB, DDD, CCC, AAA 333