The Effects of Scale and Distribution on a Deep Neural Network Iterative Classification System of Spatial Data Streams

Author:

Clarke Kurt,Osborn WendyORCID

Publisher

Springer Nature Switzerland

Reference16 articles.

1. de Brébisson, A., Vincent, P.: An exploration of softmax alternatives belonging to the spherical loss family. In: Bengio, Y., LeCun, Y. (eds.) 4th International Conference on Learning Representations, ICLR 2016, San Juan, Puerto Rico, May 2-4, 2016, Conference Track Proceedings (2016)

2. Daghistani, A., Aref, W.G., Ghafoor, A.: TrioStat: online workload estimation in distributed spatial data streaming systems. In: Proceedings of the 28th International Conference on Advances in Geographic Information Systems, pp. 78–86 (2020)

3. Ding, Q., Ding, Q., Perrizo, W.: Decision tree classification of spatial data streams using peano count trees. In: Proceedings of the 2002 ACM Symposium on Applied Computing, pp. 413–417 (2002)

4. Gomes, H.M., Read, J., Bifet, A., Barddal, J.P., Gama, J.: Machine learning for streaming data: state of the art, challenges and opportunities. ACM SIGKDD Explor. Newlett. 21(2), 6–22 (2019)

5. Hershberger, J., Shrivastava, N., Suri, S.: Summarizing spatial data streams using clusterHulls. ACM J. Exp. Algorithms 13(2), 1–28 (2009)

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