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Organizing all TSTAT studies for data, ML models for classifiers of TCP anomalies and designing better TCP designs for Science

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TCPprotocolstudy

Organizing all TSTAT studies for data, ML models for classifiers of TCP anomalies and designing better TCP designs for Science

CLASSIFIERS:

  • Decision tree classifer
  • k means classifier

DATA SETS:

  • Indis_2019: Data used for INDIS paper "G. Papadimitriou, M. Kiran, C. Wang, A. Mandal and E. Deelman, "Training Classifiers to Identify TCP Signatures in Scientific Workflows," 2019 IEEE/ACM Innovating the Network for Data-Intensive Science (INDIS), 2019, pp. 61-68, doi: 10.1109/INDIS49552.2019.00012."

ML models:

  • isolation forest
  • decision tree
  • k means analysis and silhoutte calculations

General analysis:

  • tSNE analysis
  • SHAP analysis

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Organizing all TSTAT studies for data, ML models for classifiers of TCP anomalies and designing better TCP designs for Science

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