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anyone know how is "StochasticDualCoordinateAscentClassifier()" working? is there any explanation for that? I cant understand how it's working in the background.
Is it a neural net model or some other model?
The method certainly can be applied as an SVM if you apply the method on the binary classifier with the HingeLossSDCAClassificationLossFunction. However by default it is logistic loss, that is, LogLossSDCAClassificationLossFunction.
...aaaand despite the fact that my name is right there in the paper and all they had to do was copy-paste it, I see whoever put this page together still managed to misspell my name "Finely." That's a great start to my day. 😄
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jwood803 commentedon Jun 19, 2018
I take it from this paper that it looks like it's a way to perform a Support Vector Machines (SVM) algorithm.
TomFinley commentedon Jun 19, 2018
Hi @jwood803 and @bs6523 .
The method certainly can be applied as an SVM if you apply the method on the binary classifier with the
HingeLossSDCAClassificationLossFunction. However by default it is logistic loss, that is,LogLossSDCAClassificationLossFunction.There's a paper here about this method in particular.
...aaaand despite the fact that my name is right there in the paper and all they had to do was copy-paste it, I see whoever put this page together still managed to misspell my name "Finely." That's a great start to my day. 😄
glebuk commentedon Jun 19, 2018
@bs6523,
Simply put, SDCA is a fast, scalable, multicore linear classifier with support for L1 and L2 regularization.
abgoswam commentedon Oct 18, 2018
DRI RESPONSE: Questions seems to have been answered. I plan to close the issue withing the next few days.
fix few bugs in progressbar and verbosity (dotnet#374)
code migration from machinelearning-automl to machinelearning repo fe…
fix few bugs in progressbar and verbosity (dotnet#374)
Added onnx export functionality for LpNormNormalizingTransformer (#4161)
Added Onnx export functionality to PCATransformer (#4188)