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Full-Text Articles in Physical Sciences and Mathematics
On The Role Of Genetic Algorithms In The Pattern Recognition Task Of Classification, Isaac Ben Sherman
On The Role Of Genetic Algorithms In The Pattern Recognition Task Of Classification, Isaac Ben Sherman
Masters Theses
In this dissertation we ask, formulate an apparatus for answering, and answer the following three questions: Where do Genetic Algorithms fit in the greater scheme of pattern recognition? Given primitive mechanics, can Genetic Algorithms match or exceed the performance of theoretically-based methods? Can we build a generic universal Genetic Algorithm for classification? To answer these questions, we develop a genetic algorithm which optimizes MATLAB classifiers and a variable length genetic algorithm which does classification based entirely on boolean logic. We test these algorithms on disparate datasets rooted in cellular biology, music theory, and medicine. We then get results from these …
Hyper-Heuristics For The Automated Design Of Black-Box Search Algorithms, Matthew Allen Martin
Hyper-Heuristics For The Automated Design Of Black-Box Search Algorithms, Matthew Allen Martin
Masters Theses
"Within the field of Black-Box Search Algorithms (BBSAs), there is a focus on improving algorithm performance over increasingly diversified problem classes. However, these general purpose problem solvers have no guarantee to perform well on an arbitrary problem class that a practitioner needs to solve. The problem classes that the research in this thesis most applies to are difficult problems that are going to be solved multiple times. BBSAs tailored to one of these problem class can be expected to significantly outperform the more general purpose problem solvers, including canonical Evolutionary Algorithms (EAs). The first paper in this thesis explores a …
Evolving Decision Trees For The Categorization Of Software, Jasenko Hosic
Evolving Decision Trees For The Categorization Of Software, Jasenko Hosic
Masters Theses
"Current manual techniques of static reverse engineering are inefficient at providing semantic program understanding. An automated method to categorize applications was developed in order to quickly determine pertinent characteristics. Prior work in this area has had some success, but a major strength of the approach detailed in this thesis is that it produces heuristics that can be reused for quick analysis of new data. The method relies on a genetic programming algorithm to evolve decision trees which can be used to categorize software. The terminals, or leaf nodes, within the trees each contain values based on selected features from one …