Using machine learning to conduct crime linking of residential burglary
Bibliographic Data
| ID | 6431093 |
|---|---|
| Authors | Eric Halford (0000-0002-3913-1679), Ian Gibson (0000-0001-9154-8247) |
| Year | 2024 |
| Volume | 80 |
| Pages | 100716-100716 |
| Publication date | 2024-12-10 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | International journal of law, crime and justice (JOURNAL) |
| Journal identifiers | ISSN: 1756-0616 • E-ISSN: 1876-763X |
| Publisher | Elsevier BV (PUBLISHER) |
| DOI | 10.1016/j.ijlcj.2024.100716 |
| OpenAlex | W4405223883 |
| Language | EN |
| Citations received | 1 |
| References cited | 41 |
Business · Criminology · Sociology · Computer Science · Crime Patterns and Interventions · Crime, Deviance, and Social Control · Cybercrime and Law Enforcement Studies · Artificial Intelligence
Criminality of place
Variable selection using random forests
Conditional variable importance for random forests
Random Forests
When Do Offenders Commit Crime? An Analysis of Temporal Consistency in Individual Offending Patterns
A machine learning approach to police recruitment
Space–Time Patterns of Risk
Burglars on the Job, Streetlife and Residential Break-ins
Using offender crime scene behavior to link stranger sexual assaults
How Do Residential Burglars Select Target Areas
Social Change and Crime Rate Trends
| Unique citing works | 1 |
|---|---|
| Citations per year | 1 |
| Citation span | 2026 - 2026 (1) |
| Citation velocity | current |
| Highly cited | No |
| Citation types | Neutral: 1 |