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us-accidents's Introduction

Map ML Feature

How You Can Avoid Car Accident in 2020

See the post on Medium.com.

Content:

Part I. Exploratory Data Analysis

For NJ, PA & NY

For DE, FL & CA

Part II. Machine Learning to Predict Accident Severity by State

PA
PA-Montgomery
NJ
NY
DE
FL
CA

Machine Learning Algorithms:

1. Logistic Regression

2. KNN prediction

3. Decision Trees

4. Random Forest


Data source

https://www.kaggle.com/sobhanmoosavi/us-accidents

Acknowledgements

Moosavi, Sobhan, Mohammad Hossein Samavatian, Srinivasan Parthasarathy, and Rajiv Ramnath. โ€œA Countrywide Traffic Accident Dataset.โ€, 2019.

Moosavi, Sobhan, Mohammad Hossein Samavatian, Srinivasan Parthasarathy, Radu Teodorescu, and Rajiv Ramnath. "Accident Risk Prediction based on Heterogeneous Sparse Data: New Dataset and Insights." In proceedings of the 27th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM, 2019.

Author

Ronghui Zhou, [email protected]
https://github.com/RonghuiZhou

Guideline Student must have a Github repository of their project. The repository must have a README.md file that communicates the libraries used, the motivation for the project, the files in the repository with a small description of each, a summary of the results of the analysis, and necessary acknowledgements. Students should not use another student's code to complete the project, but they may use other references on the web including StackOverflow and Kaggle to complete the project.

Posts on Kaggle:
EDA for NJ_PA_NY
Machine Learning to Predict Accident Severity for PA
Machine Learning to Predict Accident Severity for PA-Montgomery

us-accidents's People

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 avatar William A. Studniarz, MBA, PMP avatar Shrinath Sutar avatar Suresh Dontha avatar

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