Published July 20, 2023 | Version 1
Dataset Restricted

Training Dataset and Trained Model for Supervised Anomaly Diagnosis

Authors/Creators

  • 1. Boston University

Description

  • train_data.hdf: This is the training dataset used to train the Random Forest Classifier model.
  • train_label.hdf: These are the anomaly labels corresponding to each application run in the training dataset.
  • parameters.json: This JSON file helps to construct all possible features (feature extraction version).
  • normal_graph_search_dictionary.json: This file contains a dictionary that helps find the healthy node based on the specific application type users select.
  • search_dataframe.csv: This CSV file contains the raw data of the healthy nodes provided in the normal_graph_search_dictionary.json file.
  • sample_data_2.csv: This is a sample dataset used for the sample data option.
  • node_anoms_sample_2.csv: This file contains the prediction results for the dataset in the sample_data_2.csv.
  • test_model.sav: This is a trained Random Forest Classifier model that was trained offline.

 

 

Files

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Researchers who are interested in accessing the datasets can send an e-mail to esencan@bu.edu.

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