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False positive is misclassifying an actual negative instance as a positive; false negative is misclassifying an actual positive instance as a negative; and true positive and true negative are the correct classifications.
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The larger the AUC, the higher the likelihood that an actual positive case will be assigned a higher probability of being positive than an actual negative case.
We propose a mixed negative instance sampling strategy to learn the weights of different joint feature representations.
Then, the database was used to label each relation instance as a positive or negative instance in both datasets.
The character of your experience is explained by an actual instance of whiteness manifesting itself in experience.
The character of one's experience is explained by an actual instance of whiteness manifesting itself in experience.
Table 3 A typical Cost Matrix which shows the misclassification cost for Positives and Negatives Actual Positive Actual Negative Predicted Positive 0 TP 1 FP Predicted Negative 5 FN 0 TN.
It is a chemical space biased toward negative instances which adds difficulty to the prediction task.
In a basic sense, it's a graph mapping positive instances and negative instances that take place in the game.
To achieve a balance between positive instances and negative instances, we randomly selected the same number of negative instances as the number of positive instances.
The predictor is trained with known positive and negative instances in an approach called supervised learning.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com