摘要
机器人与机器学习每日新闻的一位新闻记者兼新闻编辑-机器学习的最新研究结果已经发表。根据NewsRx记者从德国多特蒙德发回的消息，研究人员指出：“本文提出了一种新的可重复机器学习方法，它可以帮助理解在分位数移位的分类模型中，特征空间被划分为预测类，从而使底层的统计或机器学习模型更加可信。”使用真实的数据点（或特定的兴趣点），观察到特定特征轻微上升或下降后预测的变化。
Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news originating from Dortmund, Germany, by NewsRx correspondents, research stated, “In this article, a new kind of interp retable machine learning method is presented, which can help to understand the partition of the feature space into predicted classes in a classification model using quantile shifts, and this way make the underlying statistical or machine le arning model more trustworthy. Basically, real data points (or specific points of interest) are used and the changes of the prediction after slightly raising or decreasing specific features are observed.”
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