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Work in progress on Inductive Stream Reasoning

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While the state of the art in Machine Learning offers practitioners effective tecniques to deal with static data sets, there are only accademic results tailored to data streams. In this presentation for the 4th Stream Reasoning workshop, I report on an effort of Alessio Bernardo (a student of mines) to set up a benchmark enviroment to (i) repeat academic results, (ii) perform studies on real data for confirming the academic results, and (iii) study the research problem of "incremental rebalancing learning on evolving data streams".

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Work in progress on Inductive Stream Reasoning

  1. 1. Inductive Stream Reasoning Work on progress in Inductive Stream Reasoning Emanuele Della Valle & Alessio Bernardo Politecnico di Milano
  2. 2. Inductive Stream Reasoning Introduction Standard Machine Learning Workflow 17/04/2019 Emanuele Della Valle & Alessio Berdardo 2
  3. 3. Inductive Stream Reasoning Introduction The Concept Drift problem 17/04/2019 Emanuele Della Valle & Alessio Berdardo 3
  4. 4. Inductive Stream Reasoning Introduction An early attempts of mines • How can we determining the optimal size of the window? • What’s the correct way to perform evaluation? D.F. Barbieri, D. Braga, S. Ceri, E. Della Valle, Y. Huang, V. Tresp, A. Rettinger, H. Wermser: Deductive and Inductive Stream Reasoning for Semantic Social Media Analytics. IEEE Intelligent Systems 25(6): 32-41 (2010) 17/04/2019 Emanuele Della Valle & Alessio Berdardo 4
  5. 5. Inductive Stream Reasoning Introduction Adaptive Sliding Window (ADWIN) 17/04/2019 Emanuele Della Valle & Alessio Berdardo 5 Bifet, A. and Gavaldà, R., 2009, August. Adaptive learning from evolving data streams. In International Symposium on Intelligent Data Analysis (pp. 249-260). Springer
  6. 6. Inductive Stream Reasoning Introduction Concept Drift and Streaming Machine Learning 17/04/2019 Emanuele Della Valle & Alessio Berdardo 6 • Hoeffding Adaptive Tree • Adaptive Random Forest • Temporally Augmented Classifier A. Bifet, R. Gavaldà, G. Holmes, B. Pfahringer: Machine Learning for Data Streams: with Practical Examples in MOA. The MIT Press (March 2, 2018)
  7. 7. Inductive Stream Reasoning Introduction Prequential Evaluation 17/04/2019 Emanuele Della Valle & Alessio Berdardo 7 Gama, J., Sebastião, R. and Rodrigues, P.P.: Issues in evaluation of stream learning algorithms. In KDD (pp. 329-338). ACM, 2009, June.
  8. 8. Inductive Stream Reasoning Introduction Massive Online Analysis (MOA) 17/04/2019 Emanuele Della Valle & Alessio Berdardo 8 https://moa.cms.waikato.ac.nz/
  9. 9. Inductive Stream Reasoning Work in progress • A benchmarking environment • Usage of the benchmark environment for • a replication study • confirmation study • Research on Incremental Rebalancing Learning on Evolving Data Streams 17/04/2019 Emanuele Della Valle & Alessio Berdardo 9
  10. 10. Inductive Stream Reasoning Work in progress Benchmarking Environment (adding back validation) 17/04/2019 Emanuele Della Valle & Alessio Berdardo 10 new
  11. 11. Inductive Stream Reasoning Work in progress Replication Study 17/04/2019 Emanuele Della Valle & Alessio Berdardo 11 • Old technologies • Dataset not available • Details not clear
  12. 12. Inductive Stream Reasoning Work in progress Replication Study (Adult Dataset) 17/04/2019 Emanuele Della Valle & Alessio Berdardo 12 Existing results
  13. 13. Inductive Stream Reasoning Work in progress Replication Study (Adult Dataset) 17/04/2019 Emanuele Della Valle & Alessio Berdardo 13 Replicated results
  14. 14. Inductive Stream Reasoning Work in progress Confirmation Study 17/04/2019 Emanuele Della Valle & Alessio Berdardo 14
  15. 15. Inductive Stream Reasoning Work in progress Confirmation Study 17/04/2019 Emanuele Della Valle & Alessio Berdardo 15
  16. 16. Inductive Stream Reasoning Work in progress Confirmation Study - Validation Results 17/04/2019 Emanuele Della Valle & Alessio Berdardo 16
  17. 17. Inductive Stream Reasoning Work in progress Incremental Rebalancing Learning on Evolving Data Streams 17/04/2019 Emanuele Della Valle & Alessio Berdardo 17
  18. 18. Inductive Stream Reasoning Work in progress Incremental Rebalancing Learning on Evolving Data Streams 17/04/2019 Emanuele Della Valle & Alessio Berdardo 18 Assumption: availability of a finite static batch of data Chawla, Nitesh V., et al. SMOTE: synthetic minority over-sampling technique. Journal of artificial intelligence research 16 (2002): 321-357.
  19. 19. Inductive Stream Reasoning Work in progress RebalanceStream Algorithm 17/04/2019 Emanuele Della Valle & Alessio Berdardo 19 [sources https://github.com/alessiobernardo/RebalanceDataStream ]
  20. 20. Inductive Stream Reasoning Research Environment Prequential Evaluation Results of RebalanceStream Algorithm 17/04/2019 Emanuele Della Valle & Alessio Berdardo 20 Modeling Code GenerationFeature Development Modeling Code GenerationConflict Resolution Balancelevel
  21. 21. Inductive Stream Reasoning Research Environment RebalanceStream+ 17/04/2019 Emanuele Della Valle & Alessio Berdardo 21
  22. 22. Inductive Stream Reasoning Research Environment Prequential Evaluation Results of RebalanceStream+ Algorithm 17/04/2019 Emanuele Della Valle & Alessio Berdardo 22 Modeling Code GenerationFeature Development Modeling Code GenerationConflict Resolution Balancelevel
  23. 23. Inductive Stream Reasoning Conclusions 17/04/2019 Emanuele Della Valle & Alessio Berdardo 23  Benchmarking environment that respects all the key features  Replication study results are similar to the existing ones  Confirmation study results are similar to standard ones for prequential evaluation, but validation tells a different story  RebalanceStream appears as a small but promising step forward
  24. 24. Inductive Stream Reasoning Future Work 17/04/2019 Emanuele Della Valle & Alessio Berdardo 24  In benchmarking environment, introduce throughput and latency as metrics  In replication study, making replicable all the experiments presented in literature  In confirmation study, understanding why the validation stream tells such a different story  On the long term, add back deductive reasoning
  25. 25. Inductive Stream Reasoning Thank you! Any Question? Emanuele Della Valle @manudellavalle http://emanueledellavalle.org

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