Date of Award

Spring 6-6-2019

Document Type

Honors Project

University Scholars Director

Dr. Christine Chaney

First Advisor/Committee Member

Dr. Carlos Arias

Second Advisor/Committee Member

Dr. John Hossler

Keywords

Crime, Machine Learning, Visualization, Research

Abstract

This article examines the implications of machine learning algorithms and models, and the significance of their construction when investigating criminal data. It uses machine learning models and tools to store, clean and analyze data that is fed into a machine learning model. This model is then compared to another model to test for accuracy, biases and patterns that are detected in between the experiments. The data was collected from data.seattle.gov and was published by the City of Seattle Data Portal and was accessed on September 17, 2018. This research will be looking into how machine learning models can be used to generate predictions and how the data management will introduce a bias that is unavoidable. This bias will be discussed, as well as the importance of understanding this bias for sensitive data, such as this crime data.

Comments

A project submitted in partial fulfillment

of the requirements of the University Scholars Honors Program

Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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