Table 6.
Systems for behavior recognition reporting classification performance
| Publication/System | Species | Behaviours | Classifier | Accuracy | Recall | Precision |
|---|---|---|---|---|---|---|
| Crispim‐Junior et al. (2017) | Rat | 4 locomotion, immobility, rearing, grooming | Multilayer Perceptron Networks | AUC of ROC: 83.6%–97.6% | ||
| van den Boom et al. (2017) | Mouse | 1 self‐grooming | Additive logistic regression | 83.3% | ||
| Farah et al. (2016) |
Rat Mouse |
3 exploring, rearing, static | SVM (multiple) | Success rate: 87% | Mean recognition rate: 57%–100% | |
| Belic et al. (2015) | Rat | 2 awake resting, actively behaving | SVM | 87%–91% | 85%–93% | |
| Wang et al. (2015) | Rat | 5 | SVM | 89% | ||
| Chanchanachitkul et al. (2013) | Rat | 2 walking, other behaviour | Neural Networks | 73% | ||
| van Dam et al., 2013; | Rat | 11 | Quadratic classifier | 65%–80% | 0–86% | |
| Kabra et al. (2013) | Mouse | 2 follow (social), walking | Additive logistic regression | 95.6% | ||
| CleverSys (Jhuang et al., 2010) | Mouse | 8 | ‐ | 60.9% | 64% | |
| Burgos‐Artizzu, X. P., Dollar, P., Lin, D., Anderson, D. J., & Perona, P. (2012) | Mouse | 13 | Decision trees | Average recognition rate: 66% | ||
| Zarringhalam et al. (2012) | Mouse | 8 | HMM | 76% | 45%–95% | 55%–100% |
| Jhuang et al. (2010) | Mouse | 8 | HMM SVM | 77.3% | 76.4% | |
| HomeCageScan (Steele et al., 2007) | Mouse | 17 | — | 50%–100% | ||
| Dollar et al. (2005) | Mouse | 5 | One nearest neighbour | 72% | 32%–89% | |
| Our classification based on Noldus tracking | Rat | 2 active, inactive | Logistic regression | 70.9% | 74%–76% | 91%–100% |