Panjab University-Test Data Set (PU-TDS)

Network traffic dataset is huge, varying and imbalanced because various classes are not equally distributed. Network traffic data is huge, varying and imbalanced because various classes are not equally distributed. Machine learning (ML) algorithms for traffic analysis uses the samples from this data to recommend the actions to be taken by the network administrators as well as training. Due to imbalances in dataset, it is difficult to train machine learning algorithms for traffic analysis and these may give biased or false results leading to serious degradation in performance of these algorithms.

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Cite this as

Raman Singh, Harish Kumar, R.K. Singla (2025). Dataset: Panjab University-Test Data Set (PU-TDS). https://doi.org/10.57702/vm8ggsdy

DOI retrieved: January 2, 2025

Additional Info

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Created January 2, 2025
Last update January 2, 2025
Defined In https://doi.org/10.5121/csit.2013.3704
Author Raman Singh
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Harish Kumar
R.K. Singla
Homepage https://www.researchgate.net/publication/232555111_Sampling_based_approaches_to_handle_imbalances_in_network_traffic_dataset_for_machine_learning_techniques