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How to Think Like a Data Scientist: Application of a Variable Order Markov Model to Indicators Management

机译:如何像数据科学家一样思考:将可变阶Markov模型应用于指标管理

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The growing demand for specialists in analyzing large volumes of data has led to an emerging profile of knowledge managers known as data scientists. How to address the different and complex scenarios with mathematical methods makes a difference when to apply them successfully in a dynamic environment such as the management indicators. For this reason, the authors present in this article a case study of prognostic indicators, developed in the field of finance, making use of mathematical Markov model which has prototyped in an abstract technological implementation with the capabilities to implement cases in other contexts. The purpose of the case study is to verify if the different levels of analysis of the Markov model provide knowledge to the prognosis by indicators while the application of the proposed methodology is shown. Thus, this work introduces to the threshold of a methodology that leads to one of the ways on how to think like a data scientist.
机译:在分析大量数据中,对专家的需求不断增长导致了被称为数据科学家的知识管理者的新兴概况。如何解决与数学方法的不同和复杂的方案,何时在动态环境中成功应用它们,例如管理指示符。出于这个原因,本文存在的作者是对金融领域开发的预后指标的案例研究,利用数学马尔可夫模型,这些模型在抽象的技术实现中造成了在其他环境中实施案例的能力。案例研究的目的是验证Markov模型的不同程度的分析如果显示所提出的方法的应用,则在指标上向预后提供知识。因此,这项工作介绍了一种方法的阈值,导致如何像数据科学家那样思考的方式。

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