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Do batch norm makes sense for regression problems?


Does Batch Normalization make sense for a ReLU activation function?Can Neural Networks be trained to smooth values / output the average?How can I improve my regression model?is Batch Norm a little bit stochastic by default?Batch norm: why the initial normalization?Can I treat text review analysis as a regression problem?How does Implicit Quantile-Regression Network (IQN) differ from QR-DQN?What should be the requirement for training data in order to obtain a good regression model using neural network?Neural Network Data Normalization SetupHow much batch effect is too much batch effect?













0












$begingroup$


When my network is performing regression (like DQN) it makes sense to use batchnorm in network when output of my network should vary from [0, 100000]?



one way to tackle it is to normalize output but output is used for ranking choices in RL system so scaling can lead to small numerical errors that can explode after upscaling...






regression batch-normalization







share|improve this question











$endgroup$











  • $begingroup$
    Use boosting methods :)
    $endgroup$
    – Aditya
    yesterday















0












$begingroup$


When my network is performing regression (like DQN) it makes sense to use batchnorm in network when output of my network should vary from [0, 100000]?



one way to tackle it is to normalize output but output is used for ranking choices in RL system so scaling can lead to small numerical errors that can explode after upscaling...






regression batch-normalization







share|improve this question











$endgroup$











  • $begingroup$
    Use boosting methods :)
    $endgroup$
    – Aditya
    yesterday













0












0








0





$begingroup$


When my network is performing regression (like DQN) it makes sense to use batchnorm in network when output of my network should vary from [0, 100000]?



one way to tackle it is to normalize output but output is used for ranking choices in RL system so scaling can lead to small numerical errors that can explode after upscaling...






regression batch-normalization







share|improve this question











$endgroup$




When my network is performing regression (like DQN) it makes sense to use batchnorm in network when output of my network should vary from [0, 100000]?



one way to tackle it is to normalize output but output is used for ranking choices in RL system so scaling can lead to small numerical errors that can explode after upscaling...






regression batch-normalization




regression batch-normalization






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited yesterday







quester

















asked yesterday









questerquester

212




212











  • $begingroup$
    Use boosting methods :)
    $endgroup$
    – Aditya
    yesterday
















  • $begingroup$
    Use boosting methods :)
    $endgroup$
    – Aditya
    yesterday















$begingroup$
Use boosting methods :)
$endgroup$
– Aditya
yesterday




$begingroup$
Use boosting methods :)
$endgroup$
– Aditya
yesterday










0






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