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Search results with tag "Imbalanced data"

Review of deep learning: concepts ... - Journal of Big Data

journalofbigdata.springeropen.com

ing data, Imbalanced Data, Interpretability of data, Uncertainty scaling, Catastrophic forgetting, Model compression, Overtting, Vanishing gradient problem, Exploding Gradient Problem, and Underspecication. We additionally discuss the proposed solutions tackling these issues.

  Data, Learning, Deep, Deep learning, Imbalanced data, Imbalanced

Using Random Forest to Learn Imbalanced Data

statistics.berkeley.edu

training data. In learning extremely imbalanced data, there is a significant probability that a bootstrap sample contains few or even none of the minority class, resulting in a tree with poor performance for predicting the minority class. A na¨ıve way of fixing this problem is to use a stratified bootstrap; i.e., sample with 2

  Data, Forest, Random, Imbalanced data, Imbalanced, Random forests

Facing Imbalanced Data - University of Pittsburgh

www.pitt.edu

Facing Imbalanced Data Recommendations for the Use of Performance Metrics La´szlo´ A. Jeni 1, Jeffrey F. Cohn1, 2, and Fernando De La Torre 1Carnegie Mellon University, Pittsburgh, PA, laszlo.jeni@ieee.org,ftorre@cs.cmu.edu

  University, Data, University of pittsburgh, Pittsburgh, Imbalanced data, Imbalanced

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Deep learning, Data, Imbalanced Data, Random Forest, University of Pittsburgh