Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
Results
Showing 1 to 10 of 10 for “"decision tree learning"”.
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Software fault identification via dynamic analysis and machine learning
… indicate errors. The technique generates machine learning models of run-time program properties known to expose faults, and applies these models to program properties of user-written code to classify and rank properties that may lead the user to errors. I evaluate an implementation of the …
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Automated detection of multiple sclerosis lesions in magnetic resonance images of the human brain
… statistical and symbolic approaches to machine learning. Knowledge of neuroanatomy is represented in the form of a tissue probability model. The model was constructed to provide a priori probabilities of brain tissue distribution per unit voxel in a standardized 3D 'brain space'. Use of the …
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Predicting and understanding inter-locus DNA interactions
… which features are useful. I use alternating decision trees, a type of supervised learning technique that potentially provides a more transparent relationship between features, to analyze proximal and distal genome interactions to determine the sequence and regulatory elements that are …
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On efficient approaches to the utility problem in adaptive problem solving
… manual experimentation and modification. Machine learning offers the prospect of automating this adaptation cycle, reducing the burden of domain-specific tuning and reconciling the conflicting needs of generality and efficacy. To date, however, the utility problem--the realization that adaptive …
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A Gis Investigation of Regional Geologic Controls on Mercury Deposits in the Southwest Region of Arkansas
… scale. Lithologic units were mapped using decision tree learning methods and a methodology, developed by Belt and Paxton (2005), dependant on topographic attributes unique to each rock type. A composite map of the changes in lithology, regional thrust faulting, and the deposits themselves …
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Development of New Cost-Sensitive Bayesian Network Learning Algorithms
… a review of existing research on cost-sensitive learning and identifies three common methods for developing cost-sensitive algorithms for decision tree learning. These methods are then utilised to develop three different algorithms for learning cost-sensitive Bayesian networks: (i) an indirect …
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Elliptical cost-sensitive decision tree algorithm - ECSDT
… challenging areas for data mining and machine learning. The literature reviews in this area show that most of the cost-sensitive algorithms that have been developed during the last decade were developed to solve binary classification problems where an example from the dataset will be classified …
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Bringing To Life An Ancient Urban Center At Monte Albán, Mexico: Exploiting The Synergy Between The Micro, Meso, And Macro Levels In A Complex System
… <p>First, at the macro or site level a set of decision rules for site occupation in Monte Albán Ia were generated. Monte Alban Ia is the first level of occupation associated with the site. These rules were used to suggest how the emergence of this early city fits various alternative models of …
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An Approach to Using Cognition in Wireless Networks
… optimizing the use of resources using machine learning and artificial intelligence techniques. Cognitive radio can also co-exist with legacy equipment thus acting as a bridge among heterogeneous communication systems. In this work, an approach for applying cognition in wireless networks is …