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Table 3 The prediction performance for content-based over 7 lags

From: Activity-based Twitter sampling for content-based and user-centric prediction models

  Lag \(=\) 1 Lag \(=\) 2 Lag \(=\) 3 Lag \(=\) 4 Lag \(=\) 5 Lag \(=\) 6 Lag \(=\) 7
Activity-based
 Narcotics 0.51 0.54 0.52 0.53 0.58 0.53 0.67
 Deceptive 0.65 0.52 0.57 0.64 0.65 0.62 0.51
 Criminal damage 0.43 0.6 0.7 0.65 0.6 0.56 0.54
 Burglary 0.52 0.58 0.56 0.56 0.56 0.54 0.52
 Battery 0.61 0.7 0.62 0.72 0.67 0.66 0.6
 Assault 0.46 0.47 0.57 0.52 0.5 0.54 0.56
 Prostitution 0.57 0.59 0.7 0.68 0.68 0.58 0.68
 PublicViolation 0.46 0.51 0.47 0.51 0.55 0.55 0.53
 Robbery 0.55 0.56 0.47 0.55 0.52 0.52 0.56
 Theft 0.65 0.55 0.52 0.6 0.62 0.58 0.62
 All 0.77 0.74 0.7 0.86 0.76 0.7 0.73
Random
 Narcotics 0.5 0.51 0.57 0.55 0.55 0.55 0.65
 Deceptive 0.63 0.56 0.55 0.55 0.68 0.67 0.60
 Criminal damage 0.42 0.62 0.69 0.68 0.65 0.56 0.51
 Burglary 0.53 0.5 0.52 0.53 0.57 0.54 0.52
 Battery 0.46 0.67 0.65 0.71 0.7 0.7 0.57
 Assault 0.46 0.54 0.56 0.54 0.53 0.52 0.55
 Prostitution 0.62 0.62 0.67 0.67 0.68 0.64 0.54
 PublicViolation 0.44 0.47 0.46 0.46 0.47 0.53 0.49
 Robbery 0.5 0.54 0.51 0.56 0.5 0.49 0.44
 Theft 0.57 0.57 0.56 0.53 0.61 0.58 0.55
 All 0.5 0.59 0.6 0.59 0.54 0.58 0.61
  1. The italic emphasizes show in which experiments the activity-based or random sampling performed better