Single Sample Feature Importance: An Interpretable Algorithm for Low-Level Feature Analysis

27 Nov 2019Joseph GattoRavi LankaYumi IwashitaAdrian Stoica

Have you ever wondered how your feature space is impacting the prediction of a specific sample in your dataset? In this paper, we introduce Single Sample Feature Importance (SSFI), which is an interpretable feature importance algorithm that allows for the identification of the most important features that contribute to the prediction of a single sample... (read more)

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