Skip to main content

Table 9 The AUC with and without individual dynamic feature for Theft prediction

From: Crime event prediction with dynamic features

Dynamic Features

Brisbane

New York City

[15–18)

[21–24)

[15–18)

[21–24)

wod

wd

wod

wd

wod

wd

wod

wd

Visitor Homogeneity

0.807

0.808

0.770

0.794

0.676

0.681

0.626

0.628

Visitor Entropy

0.807

0.818

0.770

0.785

0.676

0.680

0.626

0.629

Region Popularity

0.807

0.810

0.770

0.769

0.676

0.679

0.626

0.632

Visitor Ratio

0.807

0.823

0.770

0.788

0.676

0.676

0.626

0.628

Visitor Count

0.807

0.812

0.770

0.777

0.676

0.679

0.626

0.625

Observation Frequency

0.807

0.809

0.770

0.771

0.676

0.675

0.626

0.626

  1. wod: without dynamic features; wd: with dynamic features.