sus metric

回答: SUS指的是"Usability Metric for User Experience"，是一种用于评估用户体验的可用性度量指标。\[3\] SUS是一种标准化的问卷调查工具，通过用户对产品或功能的评价来衡量其可用性。它包含一系列关于用户对系统易用性的陈述，用户需要根据自己的体验程度进行评分。SUS的结果可以帮助团队了解用户对产品的满意度和改进的方向，从而追踪和提高产品的可用性。\[3\] SUS的使用需要明确与目标相关，并能够用于跟踪实现目标的进展。团队可以通过明确产品或功能的目标，确定衡量成功的信号，并构建特定的度量指标来跟踪进展。\[2\]
#### 引用[.reference_title]
- *1* *2* *3* [超全！体验度量理论2021版](https://blog.csdn.net/pmcaff2008/article/details/121240407)[target="_blank" data-report-click={"spm":"1018.2226.3001.9630","extra":{"utm_source":"vip_chatgpt_common_search_pc_result","utm_medium":"distribute.pc_search_result.none-task-cask-2~all~insert_cask~default-1-null.142^v91^control,239^v3^insert_chatgpt"}} ] [.reference_item]
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相关问题

metric learning

Metric learning is a type of machine learning technique that involves learning a metric, or a distance function, between pairs of data points in a dataset. The goal of metric learning is to learn a metric that can accurately capture the similarity or dissimilarity between pairs of data points, such that similar points are closer together in the learned metric space than dissimilar ones.

Metric learning has various applications in fields such as computer vision, natural language processing, and recommender systems. For example, in computer vision, metric learning can be used to learn a metric that can accurately measure the similarity between images, which can be used for tasks such as image retrieval or object recognition. In natural language processing, metric learning can be used to learn a metric that can measure the similarity between sentences or documents, which can be used for tasks such as text classification or information retrieval.

Some popular techniques for metric learning include siamese networks, triplet networks, and contrastive learning. These techniques involve learning a mapping function that maps input data points to a low-dimensional metric space, such that the distance between pairs of points in this space accurately reflects their similarity or dissimilarity.

metric-stash

根据提供的引用内容，我了解到metric-stash是一个Clojure库，用于将度量标准写入不同的目标，例如文件或Graphite服务器。它提供了多种度量标准编写器，包括JSON文件度量标准编写器，可以将度量标准写入JSON文件中。下面是一个使用JSON文件度量标准编写器创建度量标准的示例：

(require '[metric-stash :as m])

(def metrics
  (m/json-file-metric-writer "my-application" "logs/metrics.log"))

(m/write! metrics "my-metric" 42)

在上面的示例中，我们首先导入metric-stash库，并使用`m/json-file-metric-writer`函数创建一个JSON文件度量标准编写器。该函数需要两个参数：应用程序名称和日志文件的路径。然后，我们使用`m/write!`函数将度量标准写入文件中。该函数需要三个参数：度量标准的名称，度量标准的值和可选的时间戳。

--相关问题--:
1. metric-stash支持哪些目标？
2. 如何使用metric-stash将度量标准写入Graphite服务器