犯罪模式挖掘方法
1. 决策树分析
1.1 决策树构建
在分析犯罪数据时,采用了两折交叉验证的方法。将一部分数据用于训练和构建决策树,另一部分用于分类。以 98% 的置信因子生成的决策树,其 WEKA 生成的输出如下:
=== Run information ===
=== Classifier model (full training set) ===
Scheme: weka.classifiers.trees.J48 -C 0.98 -M 2
Test mode: 2-fold cross-validation
J48 pruned tree
—————————
PoliceRate = 1: 1 (303.0/8.0)
PoliceRate = 2
| Region = NW: 2 (3.0)
| Region = SW: 2 (8.0)
| Region = NE
| | PopulationRate = 1: 2 (0.0)
| | PopulationRate = 2: 1 (9.0/2.0)
| | PopulationRate = 3: 2 (91.0/32.0)
| Region = SE
| | PopulationRate = 1: 1 (0.0)
| | PopulationRate = 2: 1 (16.0/1.0)
| | PopulationRate = 3: 2 (45.0/22.0)
PoliceRate = 3: 2 (25.0)
=== Stratified cross-validation ===
=== Summary ===
Correctly Classi
超级会员免费看
订阅专栏 解锁全文
924

被折叠的 条评论
为什么被折叠?



