Explaining Machine Learning Models of Emotion Using the BIRAFFE Dataset
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[1] P. Lang. International affective picture system (IAPS) : affective ratings of pictures and instruction manual , 2005 .
[2] Scott Lundberg,et al. A Unified Approach to Interpreting Model Predictions , 2017, NIPS.
[3] Grzegorz J. Nalepa,et al. Prototypes of Arcade Games Enabling Affective Interaction , 2019, ICAISC.
[4] Carlos Guestrin,et al. Anchors: High-Precision Model-Agnostic Explanations , 2018, AAAI.
[5] G. A. Mendelsohn,et al. Affect grid : A single-item scale of pleasure and arousal , 1989 .
[6] Grzegorz J. Nalepa,et al. BIRAFFE: Bio-Reactions and Faces for Emotion-based Personalization , 2020, AfCAI.
[7] J. Gratch,et al. The Oxford Handbook of Affective Computing , 2014 .
[8] J. Gray,et al. PsychoPy2: Experiments in behavior made easy , 2019, Behavior Research Methods.
[9] Chengyu Liu,et al. Heart rate variability monitoring for emotion and disorders of emotion , 2019, Physiological measurement.
[10] Carlos Guestrin,et al. Model-Agnostic Interpretability of Machine Learning , 2016, ArXiv.
[11] Joost Broekens,et al. AffectButton: A method for reliable and valid affective self-report , 2013, Int. J. Hum. Comput. Stud..
[12] Pedro Larrañaga,et al. A review of feature selection techniques in bioinformatics , 2007, Bioinform..
[13] F. Shaffer,et al. An Overview of Heart Rate Variability Metrics and Norms , 2017, Front. Public Health.