Supervised Learning with Unsupervised Output Separation

  title={Supervised Learning with Unsupervised Output Separation},
  author={Nathalie Japkowicz},
In supervised learning approaches, the output labels are imposed by the knowledge engineer who prepared the data. While knowing the labels of a data set is quite useful, in cases where data points belonging to very different data distributions are agglomerated in the same class, a learning algorithm can have difficulties modeling these classes accurately. In such cases, it should be useful to separate the main classes into a number of more homogeneous subclasses. This paper assumes that the… CONTINUE READING
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