伽马回归工具

将伽马分布式严格正相关变量（目标变量）与预期会对目标变量产生影响的一个或多个变量（预测变量）相关联。

In a number of applications, the values of the target variable are always strictly positive (i.e., are never zero or negative), but tend to cluster toward the lower range of the observed values, but in a small minority of cases take on large values. Target variables of this nature represent a data generation process that is not consistent with the Normality assumptions underlying the traditional linear regression model. However, the values are always positive and will not always be integer numbers, so they do not follow a Poisson distribution or Negative Binomial distribution based process. They are consistent with a process based on a Gamma distribution and can be estimated using methods similar to linear regression, via the generalized linear model framework.

借助此工具，如果输入数据来自常规 Alteryx 数据流，则使用开源的 R glm 函数进行模型估计。如果输入来自 XDF 输入工具或 XDF 输出工具，则使用 Revo ScaleR rxGlm 函数进行模型估计。使用基于 Revo ScaleR 的函数的优势在于，它允许分析更大（超过内存）的数据集，但代价是创建 XDF 文件需要额外开销，无法创建开源 R 函数提供的某些模型诊断输出，并且只能生成泊松回归模型。

此工具使用 R 工具。转至选项下载预测工具，并登录到 Alteryx 下载和许可证门户以安装 R 工具和 R 工具使用的软件包。请访问下载和使用预测工具。