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SYSTEM AND METHOD FOR DATA VISUALIZATION USING MACHINE LEARNING AND AUTOMATIC INSIGHT OF FACTS ASSOCIATED WITH A SET OF DATA

机译:使用机器学习的数据可视化系统和方法,并自动识别与一组数据相关联的事实

摘要

In accordance with various embodiments, described herein are systems and methods for use of computer-implemented machine learning to automatically determine insights of facts, segments, outliers, or other information associated with a set of data, for use in generating visualizations of the data. In accordance with an embodiment, the system can receive a data set that includes data points having data values and attributes, and a target attribute, and use a machine learning process to automatically determine one or more other attributes as driving factors for the target attribute, based on, for example, the use of a decision tree and a comparison of information gain, Gini, or other indices associated with attributes in the data set. Information describing facts associated with the data set can be graphically displayed at a user interface, as visualizations, and used as a starting point for further analysis of the data set.
机译:根据各种实施例,这里描述的是用于使用计算机实现的机器学习的系统和方法,以自动确定事实,段,异常值或与一组数据相关联的其他信息的洞察,以用于生成数据的可视化。 根据一个实施例,系统可以接收包括具有数据值和属性的数据点的数据集,以及目标属性,并使用机器学习过程自动确定一个或多个其他属性作为目标属性的驱动因子, 基于例如,使用决策树和信息增益,GINI或与数据集中的属性相关联的其他索引的使用。 描述与数据集关联的事实的信息可以在用户界面中以图形方式显示为可视化,并用作进一步分析数据集的起点。

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