Body: <p>I have a very imbalanced dataset of two classes: 2% for the first class and 98% for the second. Such imbalance does not make training easy and so balancing the data set by undersampling class 2 seemed like a good idea. </p>
  
  <p>However, as I think about it, should not the machine learning algorithm expect the same data distribution in nature as in its training set? I know, for sure, that the distribution of data in nature matches my imbalanced dataset. Does that mean that the balanced dataset will negatively affect the neural net performance with testing? when it assumed a different distribution of data caused by my balanced data set. </p>
  
Tags: <neural-networks><machine-learning><deep-learning>
Title: Does balancing the training data set distribution for a neural network affect its understanding of the original distribution of data?
UserDisplayName: Robot0110
ThreadText: # Does balancing the training data set distribution for a neural network affect its understanding of the original distribution of data?
  
  (Asked by: username_0 on 2018-09-17)
  
  I have a very imbalanced dataset of two classes: 2% for the first class and 98% for the second. Such imbalance does not make training easy and so balancing the data set by undersampling class 2 seemed like a good idea.
  
  However, as I think about it, should not the machine learning algorithm expect the same data distribution in nature as in its training set? I know, for sure, that the distribution of data in nature matches my imbalanced dataset. Does that mean that the balanced dataset will negatively affect the neural net performance with testing? when it assumed a different distribution of data caused by my balanced data set.
  
  **Tags:** neural-networks, machine-learning, deep-learning
  
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  ## 0 answers
  
  