methodology-6
Model Selection
3260 papers • 126 benchmarks • 313 datasets
Given a set of candidate models, the goal of Model Selection is to select the model that best approximates the observed data and captures its underlying regularities. Model Selection criteria are defined such that they strike a balance between the goodness of fit, and the generalizability or complexity of the models. Source: Kernel-based Information Criterion
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Most implemented papers
BERTScore: Evaluating Text Generation with BERT
Tianyi Zhang, Felix Wu, Kilian Q. Weinberger, Yoav Artzi, Varsha Kishore•Sat Apr 20 2019
This work proposes BERTScore, an automatic evaluation metric for text generation that correlates better with human judgments and provides stronger model selection performance than existing metrics.
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