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模型监视器

Model Monitor
课程网址: http://videolectures.net/mloss08_raeder_mm/  
主讲教师: Troy William Raeder
开课单位: 圣母大学
开课时间: 2008-12-20
课程语种: 英语
中文简介:
机器学习中的常见做法通常隐含地假设一个固定的分布,这意味着特定特征的分布不会随着时间而改变。然而,在实践中,这种假设经常被违反,因此必须对现实世界的模型进行再培训。那么,能够预测和计划分配的变化将有助于避免这种再培训。 Model Monitor是一个解决此问题的Javatoolkit。它提供了检测数据分布变化的方法,比较分布变化下多个分类的性能,并评估个体分类对分布变化的稳健性。因此,它允许用户在许多潜在场景下确定其数据的最佳模型(或模型)。此外,Model Monitor与WEKAmachine学习环境完全集成,因此如果需要,可以使用各种商品分类器。
课程简介: Common practice in Machine Learning often implicitly assumes a stationary distribution, meaning that the distribution of a particular feature does not change over time. In practice, however, this assumption is often violated and real-world models have to be retrained as a result. It would be helpful, then, to be able to anticipate and plan for changes in distribution in order to avoid this retraining. Model Monitor is a Java toolkit that addresses this problem. It provides methods for detecting distribution shifts in data, comparing the performance of multiple classifiers under shifts in distribution, and evaluating the robustness of individual classifiers to distribution change. As such, it allows users to determine the best model (or models) for their data under a number of potential scenarios. Additionally, Model Monitor is fully integrated with the WEKA machine learning environment, so that a variety of commodity classifiers can be used if desired.
关 键 词: 机器学习; 现实世界; 个体分类
课程来源: 视频讲座网
最后编审: 2019-07-02:cwx
阅读次数: 74