Which evaluation metric is most appropriate for assessing the performance of an

Which evaluation metric is most appropriate for assessing the performance of an SVM classifier?

Which evaluation metric is most appropriate for assessing the performance of an SVM classifier?

Step 1: Understand what an SVM classifier is. It is a type of machine learning model used for classification tasks.
Step 2: Know that when we want to see how well a classifier is performing, we use evaluation metrics.
Step 3: Identify common evaluation metrics for classification, such as accuracy, precision, recall, and F1 score.
Step 4: Recognize that accuracy measures the proportion of correct predictions made by the classifier.
Step 5: Conclude that accuracy is a suitable and common metric to assess the performance of an SVM classifier.

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