Logistic Localized Modeling of the Sample Space for Feature Selection and Classification

@article{Armanfard2018LogisticLM,
  title={Logistic Localized Modeling of the Sample Space for Feature Selection and Classification},
  author={Narges Armanfard and James P. Reilly and Majid Komeili},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2018},
  volume={29},
  pages={1396-1413}
}
Conventional feature selection algorithms assign a single common feature set to all regions of the sample space. In contrast, this paper proposes a novel algorithm for localized feature selection for which each region of the sample space is characterized by its individual distinct feature subset that may vary in size and membership. This approach can… CONTINUE READING