MLF:机器学习框架
“Machine Learning Framework”常缩写为MLF,这种简称便于日常书写与交流。作为机器学习领域的核心概念,它广泛应用于社会及教育等多个场景。其中文全称为“机器学习框架”,主要用于提供算法模型开发和部署的基础架构。
Machine Learning Framework具体释义
Machine Learning Framework的英文发音
例句
- Probabilistic graphical model and variational inference is a new machine learning framework, and is a good method applied to uncertain problem or complex problem. It is applied in computer vision and natural language processing widely.
- 概率图模型和变分推理是一个新型的机器学习框架(MLF),是处理不确定性和复杂性问题的有力工具,被广泛应用于计算机视觉和自然语言处理等领域。
- As multi-instance learning has unique characters and well application prospect, multi-instance learning is called the fourth machine learning framework with supervised learning, unsupervised learning and reinforcement learning, and it has caused the extensive concern to many researchers.
- 由于多示例学习本身独特的性质和良好的应用前景,被称为是与监督学习、非监督学习和强化学习并列的第四种机器学习框架(MLF),并起了国内外研究者的极大关注。
- Mind Evolution Based Machine Learning Framework(MLF) and New Development
- 基于思维进化机器学习的框架及新进展
- Multiple-Instance learning is the forth machine learning framework after supervised learning, unsupervised learning and reinforce learning, which has been used in medicine design, image retrieval and other research fields, and expected results is available.
- 多示例学习是与监督学习、非监督学习和强化学习并列的第四类学习框架,目前已广泛应用于药物设计、图像搜索等领域,并已获得很好的效果。
- As a result, we concentrate on three types in machine learning framework, which can decrease the complexity of these algorithms.
- 因此在机器学习的识别框架中,集中处理人名、地名、组织机构名三种类型的命名实体,减少机器学习算法的复杂度。
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