原文传递
Data Mining to Improve Traffic Safety.
| 题名： | Data Mining to Improve Traffic Safety. |
| 关键词： | *Traffic-safety; *Traffic-data-analysis.;Algorithms-; Ranking-; Accident-rates. |
| 摘要： | The ever increasing size of datasets used for data mining and machine learning applications has placed a renewed emphasis on algorithm performance and processing strategies. This research addresses algorithms for ranking variables in a dataset, as well as for ranking values of a specific variable. We propose two new techniques, called Max Gain (MG) and Sum Max Gain Ratio (SMGR), which are well-correlated with existing techniques, yet are much more intuitive. MG and SMGR were developed for the public safety domain using categorical traffic accident data. Unlike the typical abstract statistical techniques for ranking variables and values, the proposed techniques can be motivated as useful intuitive metrics for non-statistician practitioners in a particular domain. Additionally, the developed techniques are generally more efficient than the more traditional statistical approaches. |
| 报告类型： | 科技报告 |
相关文献
- Integration of Crash, Pavement, ADT and Friction Data For the State of Alabama. Final rept. 10 Jun 01-31 Dec 02.
- Mining and Analysis of Traffic Safety and Roadway Condition Data.
- Techniques for Mining Truck Data to Improve Freight Operations and Planning.
- Data Mining Tools Make Flights Safer, More Efficient.
- Mining and Analysis of Traffic Safety and Roadway Condition Data. Final rept. (January 1, 2004-February 1,2005).
检索历史
应用推荐
