The project had three goals:

1. Predict TriMet ridership by bus line more accurately than current model
2. Create an interface to create predictions of ridership in the future.
3. Identify bus lines that are similar to one another

Data for the project was provided by TriMet and augmented with additional sources to describe 82 bus lines.

• 178 possible variables to predict and describe the 82 bus routes
• Variables on population, line characteristics, crime, and race
• Only about 4% of the data was missing and was imputed

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Date:

Jan-Mar 2016

Skills Related:

Data Munging, R, Shiny, GIS, Exploratory Analysis

Client:

TriMet

Website:

TriMet Ridership Projection App