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jeremiedb / mxnet_R_bucketing

R model API to support bucketing and masking
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RNN for regression #4

Closed bmkor closed 6 years ago

bmkor commented 7 years ago

Wanna know if I can change softmaxoutput to regression(linear) to do regression?

jeremiedb commented 7 years ago

Absolutely. It will also requires to change the number of hidden neurons in the previous fully connected operator to 1 (instead of the number of labels).

bmkor commented 7 years ago

Thanks. The embedding layer will not be needed right? Also, will the train data be in the shape (batch.size, num.variates * seq.len)?

jeremiedb commented 7 years ago

If your data needs no embedding (or has use pre-embedded), then the data feed should be Features X Batch X Seq.Length. You can refer to the shapes of the graph in the Readme following the Embedding operator.

bmkor commented 7 years ago

Thanks. Wondering if the shape Batch X Seq.Length shown in the graph is different from the Seq.Length X Batch used in the tutorial Char RNN example?

jeremiedb commented 7 years ago

It is effectively different from the tutorial, the RNN refactor involves some changes compared to current RNN functionnalities in the R package. The reason being that the Batch X Seq.Length is the format expected by the the symbol.RNN operator. I also suggest to consider the data preparation presented in this bucketing demo as it performs the indexing of words using a vectorized apprach rather than with loops which is much faster.

bmkor commented 6 years ago

Thanks a lot! Wanna know if I can try to make it capable of doing regression by a pull request?

jeremiedb commented 6 years ago

Hello, there were a few things I changed following various comments and I think the following push should make the regression easier to perform: https://github.com/apache/incubator-mxnet/pull/8121

Feel free to bring changes/comment or suggest another approach.

bmkor commented 6 years ago

Cool. Definitely will try.