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https://issues.apache.org/jira/browse/SOLR-11597?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16302235#comment-16302235
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Yuki Yano commented on SOLR-11597:
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Hi [~cpoerschke] and [~malcorn_redhat].
Thank you for letting me know this issue. In my opinion, [Christine's
format|https://github.com/cpoerschke/lucene-solr/blob/master-solr-11597/solr/contrib/ltr/src/java/org/apache/solr/ltr/model/NeuralNetworkModel.java#L44-L67]
looks good because of the readability.
By the way, there are some points which concern me.
1. The name of "nonlinearity" is a bit curious for me because we call these
functions as "activation function". How about using "activation" instead of
''nonlinearity" to represent it?
2. If we think to apply this to more complex neural networks in the future, we
will need to support layers (ex. convolutional and pooling) other than the full
connected layer (ex. ReLU). One possibility is that we add a "type" parameter
to represent a role of each layer like [the prototxt of Caffe's
layer|http://caffe.berkeleyvision.org/tutorial/layers.html] for future
extensions.
{code}
"layers" : [
[
{ "weights" : [ 1.0, 2.0, 3.0 ], "bias" : 4.0, "type" : "relu" },
{ "weights" : [ 5.0, 6.0, 7.0 ], "bias" : 8.0, "type" : "relu" },
{ "weights" : [ 9.0, 10.0, 11.0 ], "bias" : 12.0, "type" : "relu" },
{ "weights" : [ 13.0, 14.0, 15.0 ], "bias" : 16.0, "type" : "relu" }
],
[
{ "weights" : [ 13.0, 14.0, 15.0, 16.0 ], "bias" : 17.0, "type" : "relu" },
{ "weights" : [ 18.0, 19.0, 20.0, 21.0 ], "bias" : 22.0, "type" : "relu" }
]
]
{code}
On the other hand, this representation is redundant at this time (like
RankNet). What do you think?
> Implement RankNet.
> ------------------
>
> Key: SOLR-11597
> URL: https://issues.apache.org/jira/browse/SOLR-11597
> Project: Solr
> Issue Type: New Feature
> Security Level: Public(Default Security Level. Issues are Public)
> Components: contrib - LTR
> Reporter: Michael A. Alcorn
>
> Implement RankNet as described in [this
> tutorial|https://github.com/airalcorn2/Solr-LTR].
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