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Full-Text Articles in Other Applied Mathematics
Data And Algorithmic Modeling Approaches To Count Data, Andraya Hack
Data And Algorithmic Modeling Approaches To Count Data, Andraya Hack
Honors College Theses
Various techniques are used to create predictions based on count data. This type of data takes the form of a non-negative integers such as the number of claims an insurance policy holder may make. These predictions can allow people to prepare for likely outcomes. Thus, it is important to know how accurate the predictions are. Traditional statistical approaches for predicting count data include Poisson regression as well as negative binomial regression. Both methods also have a zero-inflated version that can be used when the data has an overabundance of zeros. Another procedure is to use computer algorithms, also known as …
The “Knapsack Problem” Workbook: An Exploration Of Topics In Computer Science, Steven Cosares
The “Knapsack Problem” Workbook: An Exploration Of Topics In Computer Science, Steven Cosares
Open Educational Resources
This workbook provides discussions, programming assignments, projects, and class exercises revolving around the “Knapsack Problem” (KP), which is widely a recognized model that is taught within a typical Computer Science curriculum. Throughout these discussions, we use KP to introduce or review topics found in courses covering topics in Discrete Mathematics, Mathematical Programming, Data Structures, Algorithms, Computational Complexity, etc. Because of the broad range of subjects discussed, this workbook and the accompanying spreadsheet files might be used as part of some CS capstone experience. Otherwise, we recommend that individual sections be used, as needed, for exercises relevant to a course in …
Fast Monte Carlo Algorithms For Computing A Low-Rank Approximation To A Matrix, Vlad S. Burca
Fast Monte Carlo Algorithms For Computing A Low-Rank Approximation To A Matrix, Vlad S. Burca
Senior Theses and Projects
Many of today's applications deal with big quantities of data; from DNA analysis algorithms, to image processing and movie recommendation algorithms. Most of these systems store the data in very large matrices. In order to perform analysis on the collected data, these big matrices have to be stored in the RAM (random-access memory) of the computing system. But this is a very expensive process since RAM is a scarce computational resource. Ideally, one would like to be able to store most of the data matrices on the memory disk (hard disk drive) while loading only the necessary parts of the …