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Full-Text Articles in Computer Sciences
A Description Of A Humans Knowledge Using Artificial Intelligence, Dj Price
A Description Of A Humans Knowledge Using Artificial Intelligence, Dj Price
Mahurin Honors College Capstone Experience/Thesis Projects
There currently does not exist a way to easily view the relationships between a collection of written items (e.g. sports articles, diary entries, research papers). In recent years, novel machine learning methods have been developed which are very good at extracting semantic relationships from large numbers of documents. One of them is the (unsupervised) machine learning model Doc2Vec which constructs vectors for documents. The research project detailed in this paper uses this and other already existing algorithms to analyze the relationship between pieces of text. We set forth a broader ambition for this project before discussing the use and need …
A Comparative Study Of Threshold-Based Feature Selection Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse
A Comparative Study Of Threshold-Based Feature Selection Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse
Dr. Huanjing Wang
Abstract Given high-dimensional software measurement data, researchers and practitioners often use feature (metric) selection techniques to improve the performance of software quality classification models. This paper presents our newly proposed threshold-based feature selection techniques, comparing the performance of these techniques by building classification models using five commonly used classifiers. In order to evaluate the effectiveness of different feature selection techniques, the models are evaluated using eight different performance metrics separately since a given performance metric usually captures only one aspect of the classification performance. All experiments are conducted on three Eclipse data sets with different levels of class imbalance. The …
A Comparative Study Of Threshold-Based Feature Selection Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse
A Comparative Study Of Threshold-Based Feature Selection Techniques, Huanjing Wang, Taghi M. Khoshgoftaar, Jason Van Hulse
Computer Science Faculty Publications
Abstract Given high-dimensional software measurement data, researchers and practitioners often use feature (metric) selection techniques to improve the performance of software quality classification models. This paper presents our newly proposed threshold-based feature selection techniques, comparing the performance of these techniques by building classification models using five commonly used classifiers. In order to evaluate the effectiveness of different feature selection techniques, the models are evaluated using eight different performance metrics separately since a given performance metric usually captures only one aspect of the classification performance. All experiments are conducted on three Eclipse data sets with different levels of class imbalance. The …