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arXiv:1703.10449physics.pop-ph

A Neural Networks Approach to Predicting How Things Might Have Turned Out Had I Mustered the Nerve to Ask Barry Cottonfield to the Junior Prom Back in 1997

Eve Armstrong

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Abstract

We use a feed-forward artificial neural network with back-propagation through a single hidden layer to predict Barry Cottonfield's likely reply to this author's invitation to the "Once Upon a Daydream" junior prom at the Conard High School gymnasium back in 1997. To examine the network's ability to generalize to such a situation beyond specific training scenarios, we use a L2 regularization term in the cost function and examine performance over a range of regularization strengths. In addition, we examine the nonsensical decision-making strategies that emerge in Barry at times when he has recently engaged in a fight with his annoying kid sister Janice. To simulate Barry's inability to learn efficiently from large mistakes (an observation well documented by his algebra teacher during sophomore year), we choose a simple quadratic form for the cost function, so that the weight update magnitude is not necessary correlated with the magnitude of output error. Network performance on test data indicates that this author would have received an 87.2 (1)% chance of "Yes" given a particular set of environmental input parameters. Most critically, the optimal method of question delivery is found to be Secret Note rather than Verbal Speech. There also exists mild evidence that wearing a burgundy mini-dress might have helped. The network performs comparably for all values of regularization strength, which suggests that the nature of noise in a high school hallway during passing time does not affect much of anything. We comment on possible biases inherent in the output, implications regarding the functionality of a real biological network, and future directions. Over-training is also discussed, although the linear algebra teacher assures us that in Barry's case this is not possible.

arXiv comments
10 pages, 4 figures
Journal reference
DOI
Subjects
physics.pop-phPopular Physics q-bio.NCNeurons and Cognition

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