[[["이해하기 쉬움","easyToUnderstand","thumb-up"],["문제가 해결됨","solvedMyProblem","thumb-up"],["기타","otherUp","thumb-up"]],[["이해하기 어려움","hardToUnderstand","thumb-down"],["잘못된 정보 또는 샘플 코드","incorrectInformationOrSampleCode","thumb-down"],["필요한 정보/샘플이 없음","missingTheInformationSamplesINeed","thumb-down"],["번역 문제","translationIssue","thumb-down"],["기타","otherDown","thumb-down"]],["최종 업데이트: 2025-09-04(UTC)"],[],[],null,["# Improve explanations for AutoML image classification\n\n| **Preview**\n|\n|\n| This feature is subject to the \"Pre-GA Offerings Terms\" in the General Service Terms section\n| of the [Service Specific Terms](/terms/service-terms#1).\n|\n| Pre-GA features are available \"as is\" and might have limited support.\n|\n| For more information, see the\n| [launch stage descriptions](/products#product-launch-stages).\n\nWhen you are working with AutoML image models, you can configure\nspecific parameters to improve your explanations.\n\nThe [Vertex Explainable AI feature attribution\nmethods](/vertex-ai/docs/explainable-ai/overview#compare-methods) are all based on variants of\nShapley values. Because\nShapley values are very computationally expensive, Vertex Explainable AI provides\napproximations instead of the exact values.\n\nYou can reduce the approximation error and get closer to the exact values by\nchanging the following inputs:\n\n- Increasing the number of integral steps or number of paths.\n\n### Increasing steps\n\nTo reduce approximation error, you can increase:\n\n- the **Number of integral steps** in the UI\n\nWhat's next\n-----------\n\n- Explore the [Limitations of Vertex Explainable AI](/vertex-ai/docs/explainable-ai/limitations)."]]
