Joffrey L. Leevy

Orcid: 0000-0002-7079-7540

According to our database1, Joffrey L. Leevy authored at least 33 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Advancing machine learning with OCR2SEQ: an innovative approach to multi-modal data augmentation.
J. Big Data, December, 2024

A Review of Unsupervised Anomaly Detection Techniques for Health Insurance Fraud.
Proceedings of the 10th IEEE International Conference on Big Data Computing Service and Machine Learning Applications, 2024

2023
Threshold optimization and random undersampling for imbalanced credit card data.
J. Big Data, December, 2023

Investigating the effectiveness of one-class and binary classification for fraud detection.
J. Big Data, December, 2023

Comparative analysis of binary and one-class classification techniques for credit card fraud data.
J. Big Data, December, 2023

An approach to application-layer DoS detection.
J. Big Data, December, 2023

The effect of feature extraction and data sampling on credit card fraud detection.
J. Big Data, 2023

Assessing One-Class and Binary Classification Approaches for Identifying Medicare Fraud.
Proceedings of the 24th IEEE International Conference on Information Reuse and Integration for Data Science, 2023

One-Class Classifier Performance: Comparing Majority versus Minority Class Training.
Proceedings of the 35th IEEE International Conference on Tools with Artificial Intelligence, 2023

2022
IoT information theft prediction using ensemble feature selection.
J. Big Data, 2022

A Class-Imbalanced Study with Feature Extraction via PCA and Convolutional Autoencoder.
Proceedings of the 23rd IEEE International Conference on Information Reuse and Integration for Data Science, 2022

Evaluating Performance Metrics for Credit Card Fraud Classification.
Proceedings of the 34th IEEE International Conference on Tools with Artificial Intelligence, 2022

2021
A reconstruction error-based framework for label noise detection.
J. Big Data, 2021

Detecting cybersecurity attacks across different network features and learners.
J. Big Data, 2021

A Review and Analysis of the Bot-IoT Dataset.
Proceedings of the 15th IEEE International Conference on Service-Oriented System Engineering, 2021

Feature Extraction for Class Imbalance Using a Convolutional Autoencoder and Data Sampling.
Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

Detecting Information Theft Attacks in the Bot-IoT Dataset.
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Detecting SSH and FTP Brute Force Attacks in Big Data.
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

IoT Reconnaissance Attack Classification with Random Undersampling and Ensemble Feature Selection.
Proceedings of the 7th IEEE International Conference on Collaboration and Internet Computing, 2021

An Easy-to-Classify Approach for the Bot-IoT Dataset.
Proceedings of the Third IEEE International Conference on Cognitive Machine Intelligence, 2021

Mitigating Class Imbalance for IoT Network Intrusion Detection: A Survey.
Proceedings of the Seventh IEEE International Conference on Big Data Computing Service and Applications, 2021

2020
Survey on RNN and CRF models for de-identification of medical free text.
J. Big Data, 2020

Investigating the relationship between time and predictive model maintenance.
J. Big Data, 2020

A survey and analysis of intrusion detection models based on CSE-CIC-IDS2018 Big Data.
J. Big Data, 2020

Investigating class rarity in big data.
J. Big Data, 2020

A Short Survey of LSTM Models for De-identification of Medical Free Text.
Proceedings of the 6th IEEE International Conference on Collaboration and Internet Computing, 2020

Detecting Cybersecurity Attacks Using Different Network Features with LightGBM and XGBoost Learners.
Proceedings of the 2nd IEEE International Conference on Cognitive Machine Intelligence, 2020

2019
Examining characteristics of predictive models with imbalanced big data.
J. Big Data, 2019

Severely imbalanced Big Data challenges: investigating data sampling approaches.
J. Big Data, 2019

A Comparison of Performance Metrics with Severely Imbalanced Network Security Big Data.
Proceedings of the 20th IEEE International Conference on Information Reuse and Integration for Data Science, 2019

The Effect of Time on the Maintenance of a Predictive Model.
Proceedings of the 18th IEEE International Conference On Machine Learning And Applications, 2019

Investigating Random Undersampling and Feature Selection on Bioinformatics Big Data.
Proceedings of the IEEE Fifth International Conference on Big Data Computing Service and Applications, 2019

2018
A survey on addressing high-class imbalance in big data.
J. Big Data, 2018


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