这种方法是随意推断(casual inference)的一个例子:在没有做必要的工作来理解因果问题并处理因果假设的情况下进行推断。 Did you find this page helpful? Consider sharing it 参考文献[1] A Second Chance to Get Causal Inference Right: A Classification of Data Science Tasks: dx.doi.org/10.1080/0933 [2...
出版社:Manning 出版年:2023-12-26 页数:275 定价:USD 59.99 装帧:Paperback ISBN:9781633439658 豆瓣评分 目前无人评价 评价: 写笔记 写书评 加入购书单 分享到 推荐 内容简介· ··· Causal Inference for Data Science introduces data-centric techniques and methodologies you can use to estimate causal ...
A/B tests or randomized controlled trials are expensive and often unfeasible in a business environment. Causal Inference for Data Science reveals the techniques and methodologies you can use to identify causes from data, even when no experiment or test has been performed. In Causal Inference for D...
A/B tests or randomized controlled trials are expensive and often unfeasible in a business environment.Causal Inference for Data Sciencereveals the techniques and methodologies you can use to identify causes from data, even when no experiment or test has been performed. InCausal Inference for Data ...
These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for ...
因果推断(Causal Inference)可由两类任务组成: 因果关系挖掘(Causal Discovery):即给定一组数据,挖掘出数据属性的因果图或者因果图的一部分。 因果效应估计(Causal Effect Estimation):在得到变量因果关系的前提下,研究不同变量之间如何定量地相互影响;也可以用来定量计算出不同的因对于同一个果,谁的影响程度更大(可...
Causal inference is an essential area of study with major importance across disciplines. Allowing researchers to identify the factors leading to specific outcomes, causal inference in the field of medical research, can potentially inform medical practice and health policies, in turn improving public heal...
Causal inference provides the theoretical foundations to use data and qualitative domain knowledge to quantitatively answer these questions, complementing statistics and machine learning techniques. However, there is still a broad language gap between the methodological and domain science communities. In this...
Causal Inference in Statistics 作者:Judea Pearl 出版社:Wiley 副标题:A Primer 出版年:2016-2-19 页数:156 定价:GBP 27.99 装帧:Paperback ISBN:9781119186847 豆瓣评分 9.3 73人评价 5星 64.4% 4星 28.8% 3星 6.8% 2星 0.0% 1星 0.0% 评价:
In this section, the input variable X and the outcome variable Y are both binary. Counterfactual inference is an important part of causal inference. Briefly speaking, counterfactual inference is to determine the probability that the event y would not have occurred (y = 0) had the event x not...