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Researcher profile

Taghi M. Khoshgoftaar

6 papers in the PaperMetrix corpus

Publications

Papers by this author

  1. A survey on Image Data Augmentation for Deep Learning

    2019 · Journal Of Big Data

    Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfitting. Overfitting refers to the phenomenon when a network learns a …

  2. A survey of transfer learning

    2016 · Journal Of Big Data

    Machine learning and data mining techniques have been used in numerous real-world applications. An assumption of traditional machine learning methodologies is the training data and testing data are taken from the same domain, such that …

  3. Alterations to the Bootstrapping Process within Random Forest: A Case Study on Imbalanced Bioinformatics Data

    2015

    Class imbalance is a significant challenge that practitioners in the field of bioinformatics are faced with on a daily basis. It is a phenomenon that occurs when number of instances of one class is much …

  4. Stability of Three Forms of Feature Selection Methods on Software Engineering Data

    2015 · Proceedings/Proceedings of the ... International Conference on Software Engineering and Knowledge Engineering

    One of the major challenges when working with software metrics datasets is that some metrics may be redundant or irrelevant to software defect prediction. This may be addressed using feature (metric) selection, which chooses an …

  5. The Effects of Random Undersampling for Big Data Medicare Fraud Detection

    2022

    We show it is possible to obtain better classification performance for experiments involving highly imbalanced Big Data with the application of data sampling techniques. We apply Random Undersampling to a publicly available Medicare insurance claims …

  6. Improving Medicare Fraud Detection through Big Data Size Reduction Techniques

    2023

    Classification models serve as effective tools for Medicare fraud detection, but their performance can be influenced by a number of factors. This paper focuses on addressing two common challenges using the Medicare Part D Big …