About: Negative log predictive density

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In statistics, the negative log predictive density (NLPD) is a measure of error between a model's predictions and associated true values. A smaller value is better. Importantly the NLPD assesses the quality of the model's uncertainty quantification. It is used for both regression and classification. To compute: (1) find the probabilities given by the model to the true labels. (2) find the negative log of this product. (we actually find the negative of the sum of the logs, for numerical reasons).

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  • In statistics, the negative log predictive density (NLPD) is a measure of error between a model's predictions and associated true values. A smaller value is better. Importantly the NLPD assesses the quality of the model's uncertainty quantification. It is used for both regression and classification. To compute: (1) find the probabilities given by the model to the true labels. (2) find the negative log of this product. (we actually find the negative of the sum of the logs, for numerical reasons). (en)
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  • In statistics, the negative log predictive density (NLPD) is a measure of error between a model's predictions and associated true values. A smaller value is better. Importantly the NLPD assesses the quality of the model's uncertainty quantification. It is used for both regression and classification. To compute: (1) find the probabilities given by the model to the true labels. (2) find the negative log of this product. (we actually find the negative of the sum of the logs, for numerical reasons). (en)
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  • Negative log predictive density (en)
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