The Independent Sign Bias: Gaining Insight from Multiple Linear Regression
The Independent Sign Bias: Gaining Insight from Multiple Linear Regression
复制标题
独立符号偏差：从多元线性回归中获得见解
DOI：
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Stephen D. Bay
中科院分区：
文献类型：
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作者：
M. Pazzani;Stephen D. Bay
随着电子数据的广泛使用，对帮助人们从数据中获得洞察力的工具的需求已经出现。统计学、机器学习和神经网络等多种技术已被应用于数据库，以期从数据中挖掘知识。多元回归是一种通过将线性方程拟合到观测数据来对一组解释变量和因变量之间的关系进行建模的方法。在这里，我们研究并讨论了一些影响所得回归方程是否是可靠模型的因素。
As electronic data becomes widely available, the need for tools that help people gain insight from data has arisen. A variety of techniques from statistics, machine learning, and neural networks have been applied to databases in the hopes of mining knowledge from data. Multiple regression is one such method for modeling the relationship between a set of explanatory variables and a dependent variable by fitting a linear equation to observed data. Here, we investigate and discuss some factors that influence whether the resulting regression equation is a credible model of the