Understanding Public Safety Trends in Calgary through data mining
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2024
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866914893837369344 |
|---|---|
| author | Dewis, Zack Sen, Apratim Wong, Jeffrey Zhang, Yujia |
| author_facet | Dewis, Zack Sen, Apratim Wong, Jeffrey Zhang, Yujia |
| contents | This paper utilizes statistical data from various open datasets in Calgary to to uncover patterns and insights for community crimes, disorders, and traffic incidents. Community attributes like demographics, housing, and pet registration were collected and analyzed through geospatial visualization and correlation analysis. Strongly correlated features were identified using the chi-square test, and predictive models were built using association rule mining and machine learning algorithms. The findings suggest that crime rates are closely linked to factors such as population density, while pet registration has a smaller impact. This study offers valuable insights for city managers to enhance community safety strategies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_21163 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Understanding Public Safety Trends in Calgary through data mining Dewis, Zack Sen, Apratim Wong, Jeffrey Zhang, Yujia Computers and Society Artificial Intelligence This paper utilizes statistical data from various open datasets in Calgary to to uncover patterns and insights for community crimes, disorders, and traffic incidents. Community attributes like demographics, housing, and pet registration were collected and analyzed through geospatial visualization and correlation analysis. Strongly correlated features were identified using the chi-square test, and predictive models were built using association rule mining and machine learning algorithms. The findings suggest that crime rates are closely linked to factors such as population density, while pet registration has a smaller impact. This study offers valuable insights for city managers to enhance community safety strategies. |
| title | Understanding Public Safety Trends in Calgary through data mining |
| topic | Computers and Society Artificial Intelligence |
| url | https://arxiv.org/abs/2407.21163 |