Ji Yang edited this page Oct 21, 2016 · 2 revisions

Welcome to the crime-analytics wiki!

Edmonton, which is the capital city of Alberta, is a beautiful and dynamic city. But the crimes which always be considered as harmful for everyone who lives here and want to live here happen every day. Both criminology and sociology are sophisticated subjects and require a certain degree of domain knowledge and experience in order to estimate whether a place is good for living or not based on the crime amount and the crime rate. Previously, there is no objective or a statistical way to predict crime related data. In such a case, a family who wants a peaceful and sweet life may move to a neighborhood which probably is considered as "relatively high crime rate" area. The Open Data Edmonton provides us a wide range of data based on the neighborhood in the city of Edmonton.

Currently, the City of Edmonton employs machine learning to optimally place Officers where they are needed the most (https://www.edmonton.ca/city_government/initiatives_innovation/analytics.aspx). The goal of this project is to similarly apply machine learning techniques in order to reduce crime by targeting demographics that appear to be most affected. Using the City of Edmonton’s census and crime data, we will extract features that appear to be correlated with crime and identify their significance. The significance of these features can be telling of what demographic needs to be targeted in order to reduce crime (e.g. unemployment appears to have a high correlation with the crime then there should be social programs to help those unemployed).

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