在 Google Cloud 控制台中，Vertex AI 提供一个滑块，用于调整所有类别或标签或者单个类别或标签的置信度阈值。滑块显示在评估标签页的模型详情页面上。置信度阈值是模型为测试项分配类或标签时必须具有的置信度水平。通过调整阈值，您可以看到模型的精度和召回率变化。较高的阈值通常可以提高精确率，并会降低召回率。
[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-08-07。"],[],[],null,["# Interpret prediction results from image classification models\n\nAfter requesting a prediction, Vertex AI returns results based on your model's objective. AutoML single-label image classification predictions return a single label category and its corresponding confidence score. Multi- label classification predictions return multiple label categories and their corresponding confidence scores.\n\n\u003cbr /\u003e\n\n\nThe confidence score communicates how strongly your model associates each\nclass or label with a test item. The higher the number, the higher the model's\nconfidence that the label should be applied to that item. You decide how high\nthe confidence score must be for you to accept the model's results.\n\n\u003cbr /\u003e\n\n#### Score threshold slider\n\n\nIn the Google Cloud console, Vertex AI provides a slider that's\nused to adjust the confidence threshold for all classes or labels, or an\nindividual class or label. The slider is available on a model's detail page in\nthe **Evaluate** tab. The confidence threshold is the confidence level that\nthe model must have for it to assign a class or label to a test item. As you\nadjust the threshold, you can see how your model's precision and recall\nchanges. Higher thresholds typically increase precision and lower recall.\n\n\u003cbr /\u003e\n\n#### Example batch prediction output\n\nBatch AutoML image classification prediction output are stored as\n[JSON Lines](https://jsonlines.org/)\nfiles in Cloud Storage buckets. Each line of the JSON Lines file\ncontains all annotation (label) categories and their corresponding\nconfidence scores for a single image file.\n\n\n| **Note**: The following JSON Lines example includes line breaks for\n| readability. In your JSON Lines files, line breaks are included only after each\n| each JSON object.\n\n\u003cbr /\u003e\n\n\n```\n{\n \"instance\": {\"content\": \"gs://bucket/image.jpg\", \"mimeType\": \"image/jpeg\"},\n \"prediction\": {\n \"ids\": [1, 2],\n \"displayNames\": [\"cat\", \"dog\"],\n \"confidences\": [0.7, 0.5]\n }\n}\n```"]]
