？

问题如下：

Based only on Dataset XYZ’s composition and Bector’s view regarding false positive and false negative evaluation metrics, which performance measure is most appropriate?

选项：

Recall

F1 score

Precision

解释：

B is correct.

F1 score is the most appropriate performance measure for Dataset XYZ. Bector gives equal weight to false positives and false negatives. Accuracy and F1 score are overall performance measures that give equal weight to false positives and false negatives.

Accuracy is considered an appropriate performance measure for balanced datasets, where the number of “1” and “0” classes are equal.

F1 score is considered more appropriate than accuracy when there is unequal class distribution in the dataset and it is necessary to measure the equilibrium of precision and recall.

Since Dataset XYZ contains an unequal class distribution between positive and negative sentiment sentences, F1 score is the most appropriate performance measure.

Precision is the ratio of correctly predicted positive classes to all predicted positive classes and is useful in situations where the cost of false positives or Type I errors is high.

Recall is the ratio of correctly predicted positive classes to all actual positive classes and is useful in situations where the cost of false negatives or Type II errors is high.