By Colleen McCue (Auth.)
, Pages xiii-xiv
, Pages xv-xxiii
, Pages xxv-xxxi
1 - Basics
, Pages 3-18
2 - area Expertise
, Pages 19-24
3 - information Mining
, Pages 25-41
4 - strategy versions for info Mining and Analysis
, Pages 45-66
5 - Data
, Pages 67-92
6 - Operationally appropriate Preprocessing
, Pages 93-115
7 - Predictive Analytics
, Pages 117-141
8 - Public Safety-Specific Evaluation
, Pages 143-163
9 - Operationally Actionable Output
, Pages 165-174
10 - common Crime
, Pages 177-185
11 - Behavioral research of Violent Crime
, Pages 187-213
12 - danger and danger Assessment
, Pages 215-235
13 - Deployment
, Pages 239-265
14 - Surveillance Detection
, Pages 267-298
15 - complicated Topics
, Pages 301-313
16 - destiny Trends
, Pages 315-321
, Pages 323-332
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Additional info for Data Mining and Predictive Analysis. Intelligence Gathering and Crime Analysis
This is really unfortunate because most of them have excellent analytical skills. In many ways, a good investigator is an excellent analyst and a natural data miner. In fact, investigative training and process resembles case-based reasoning in many ways. 1 For example, who better understands the limitations of crime and intelligence data than the people responsible for collecting it? Who knows better what the analytical products will be used for and what they should look like? Similarly, who better to distinguish between suspicious data and data that are both valid and reliable?
For example, a young male killed in a drive-by shooting in an area known for open-air drug markets is probably the victim of a drugrelated homicide. Additional information indicating that the victim was known to be involved in drug selling will further define the motive and suggest that likely suspects will include others involved in illegal drug markets. Post-mortem information indicating that the victim had used drugs recently before his death will add additional value to our understanding of the incident.
The software has progressed to the point where it is no longer necessary to be a statistician or artificial intelligence (AI) engineer. ” This will help the user avoid some of the common analytical pitfalls covered in other chapters of this book. The most important knowledge for successful data mining is domain expertise. It has been my experience that it is relatively easy to teach crime and intelligence analysts, even those with no formal statistical training, how to use data mining software.