Missing Data Prediction and Classification: The Use of Auto-Associative Neural Networks and Optimization Algorithms

@article{Leke2014MissingDP,
  title={Missing Data Prediction and Classification: The Use of Auto-Associative Neural Networks and Optimization Algorithms},
  author={Collins Leke and Bhekisipho Twala and Tshilidzi Marwala},
  journal={ArXiv},
  year={2014},
  volume={abs/1403.5488}
}
This paper presents methods which are aimed at finding approximations to missing data in a dataset by using optimization algorithms to optimize the network parameters after which prediction and classification tasks can be performed. The optimization methods that are considered are genetic algorithm (GA), simulated annealing (SA), particle swarm optimization (PSO), random forest (RF) and negative selection (NS) and these methods are individually used in combination with auto-associative neural… CONTINUE READING

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