F1: 95.6Accuracy: 95.6
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Interpretable Machine Learning
The goal of Interpretable Machine Learning is to allow oversight and understanding of machine-learned decisions. Much of the work in Interpretable Machine Learning has come in the form of devising methods to better explain the predictions of machine learning models.
<span class="description-source">Source: Assessing the Local Interpretability of Machine Learning Models </span>
논문
JOINT-F1: 41.50NOV-F1: 38.39VAL-F1: 44.60
Macro F1: 60.25
Overall F1: 26.61
Overall F1: 32.81
Overall F1: 34.4
JOINT-F1: 43.27VAL-F1: 69.80NOV-F1: 62.43
Macro F1: 78.71
Top 1 Accuracy: 85.9
macro F1: 85.06
Top 1 Accuracy: 85.7