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Presented by Matt Brunner

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1 Presented by Matt Brunner
Evaluating Trends in Sasquatch Sightings in North America Using Neural Networks Presented by Matt Brunner

2 Adapt Data from BFRO.net into Useful Format

3 Adapt Data from BFRO.net into Useful Format

4 Narrow Focus to the Lower 48

5 Evaluation Using a Multilayer Perceptron Network
Developed using the neural network toolbox, 10 hidden nodes. Goal is to correctly classify states within their summary quantile. Poorly suited to this data set.

6 Evaluation Using K-Means Clustering
Using coordinates from population center information from U.S. Census Bureau Each data point has four dimensions: Latitude Longitude Year Number of Reports

7 Evaluation Using K-Means Clustering
K =10 Clusters K = 25 Clusters

8 Evaluation Using K-Means Clustering
2D representation of 4D data. Effect of more densely populated areas evident. Higher K values likely to align a cluster center and a population center K =50 Clusters

9 Evaluation Using K-Means Clustering

10 Conclusion K-means is a much better method for analyzing this data set compared to an MLP. Difficult to account for all variables and be able to visualize. Developing a 2D Self-Organizing Map to further explore this data.

11 Works Cited Bigfoot Field Researchers Organization. United States Census Bureau, Centers of Populations By State: _Mean_ST.txt


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