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Using Neural Networks To Classify Discrete Circular Probability Distributions, Madelyn Gaumer
Using Neural Networks To Classify Discrete Circular Probability Distributions, Madelyn Gaumer
HMC Senior Theses
Given the rise in the application of neural networks to all sorts of interesting problems, it seems natural to apply them to statistical tests. This senior thesis studies whether neural networks built to classify discrete circular probability distributions can outperform a class of well-known statistical tests for uniformity for discrete circular data that includes the Rayleigh Test1, the Watson Test2, and the Ajne Test3. Each neural network used is relatively small with no more than 3 layers: an input layer taking in discrete data sets on a circle, a hidden layer, and an output …