Top-5 accuracy is unavailable since the number of categories
时间: 2024-05-20 17:18:29 浏览: 16
is not specified. Top-5 accuracy is a metric used in machine learning to evaluate the performance of a multi-class classification model. It measures the percentage of times that the correct label is among the top 5 predicted labels. However, the number of categories or classes in the classification problem needs to be specified in order to calculate the top-5 accuracy. Without this information, it is not possible to provide a meaningful answer to the question.
相关问题
Top-5 accuracy
Top-5 accuracy is a metric used to evaluate the performance of a machine learning model in a multi-class classification problem. It measures the percentage of times that the correct label appears in the top five predictions made by the model. For example, if the correct label is "dog" and the model's top five predictions are "cat", "horse", "dog", "sheep", and "cow", then the model's top-5 accuracy is 1 (or 100%) because "dog" appears in the top five predictions. Top-5 accuracy is often used in image classification tasks where there may be multiple objects present in the image and the model needs to identify all of them.
公式top-5 accuracy=
top-5 accuracy是指在分类任务中,预测的类别在前5个中包含了真实类别的样本占全部样本的比例。其公式如下:
top-5 accuracy = (至少有一个正确分类的样本数) / (总样本数)
其中,至少有一个正确分类的样本数指的是预测的类别中包含了真实类别的样本数。总样本数指的是所有样本的数量。
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