动手进行预测分析

English | 2024 | ISBN: 9781098153168 | 300 pages | EPUB | 16.2 MB

Business decisions in any context—operational, tactical, or strategic—can have considerable consequences. Whether the outcome is positive and rewarding or negative and damaging to the business, its employees, and stakeholders is unknown when action is approved. These decisions are usually made under the proverbial cloud of uncertainty.

With this practical guide, data analysts, data scientists, and business analysts will learn why and how maximizing positive consequences and minimizing negative ones requires three forms of rich information: Descriptive analytics explores the results from an action—what has already happened. Predictive analytics focuses on what could happen. The third, prescriptive analytics, informs us what should happen in the future.

While all three are important for decision-makers, the primary focus of this book is on the third: prescriptive analytics. Author Walter R. Paczkowski, Ph.D. shows you

The distinction among descriptive, predictive, and prescriptive analytics How predictive analytics produces a menu of action options How prescriptive analytics narrows the menu of action options The forms of prescriptive analytics: eight prescriptive methods Two broad classes of these methods: non-stochastic and stochastic How to develop prescriptive analyses for action recommendations Ways to use an appropriate tool-set in Python

在任何情境下——无论是运营、战术还是战略层面——商业决策都可能产生重大后果。不论结果是积极且令人满意，还是消极且损害企业及其员工和利益相关者，一旦批准行动，其影响未知。这些决策通常是在不确定的阴影下作出的。 凭借这本实用指南，数据分析师、数据科学家及业务分析师将学会为何以及如何通过三种丰富的信息形式来最大化积极后果并减少负面后果：描述性分析会探索行动的结果——即已经发生了什么；预测性分析则关注可能发生的情况；第三种是决策性分析（prescriptive analytics），它告知我们在未来应该如何行动。 尽管这三种分析都重要，但本书主要聚焦于决策者中最重要的部分——决策性分析。作者沃伦·R·帕卡科夫博士（Walter R. Paczkowski, Ph.D.）将向您展示： 描述性、预测性和决策性分析的区分 预测性分析是如何提供行动方案菜单 决策性分析如何导航行动方案菜单 决策性分析的形式：八种决策方法 这两种方法的两大类别：非随机与随机 如何为行动计划推荐开发决策性分析 使用Python工具集的方法

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