Visualization analysis of feed forward neural network input contribution

  • Jamal A
  • Ali R
  • Nouh A
  • et al.
N/ACitations
Citations of this article
9Readers
Mendeley users who have this article in their library.

Abstract

The complexity of domain problem can slow or even hinder the learning process of neural networks. It is rather difficult to overcome such an obstacle because neural networks, as cited today in the literature, lack the interpretability of their internal structures. In this paper, we present a visualization approach capable of enhancing the understanding of neural networks. Our approach visualizes input and weight contributions, sensitivity analysis, and provides guidance in pruning less influential features and consequently reducing the complexity of domain problem while maintaining acceptable error rates. We conduct experiments on various datasets to show the effectiveness of our approach.

Cite

CITATION STYLE

APA

Jamal, A., Ali, R., Nouh, A., & Hossam, F. (2014). Visualization analysis of feed forward neural network input contribution. Scientific Research and Essays, 9(14), 645–651. https://doi.org/10.5897/sre2014.5895

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free