Box Cox Transformation
Box-Cox Transformation is located under Model Studio > Statistical Analysis > Box Cox Transformation. Alternatively, use the search bar to find the Box-Cox Transformation test feature. Use the drag-and-drop method or double-click to use the algorithm in the canvas. Click the algorithm to view and select different properties for analysis.
Properties of Box-Cox Transformation
The Box-Cox Transformation's available properties are shown in the figure below.
The following table describes the properties of box-cox transformation.
Field | Description | Remark |
Run | It allows you to run the node. | - |
Explore | It allows you to explore the successfully executed node. | - |
Vertical Ellipses | The available options are · Run till node · Run from node · Publish as a model · Publish code | - |
Task Name | It is the name of the task selected on the workbook canvas. | You can click the text field to edit or modify the task name as required. |
Dependent Variables | It allows you to select the Dependent variable | You can choose only one variable, which should be Categorical.
|
Lambda | It is a parameter that determines the type and magnitude of the transformation applied to the data. | The default value is none. |
Alpha | It refers to the transformation parameter lambda, which determines the type and extent of transformation applied to the data. | The default value is 0.05 |
Example of Box-Cox Transformation
We consider the FemaleBirth Dataset. A snippet of input data is shown below.
The Result page of Box-Cox transformation is shown below.
The result page displays the following sections
- Shapiro Wilk's Test for Normality: - It is a statistical test used to assess the normality of a data sample.
It shows the W statistics, p-value, and alpha value. Also, Depending on the p-value it shows the inference about the distribution of data.
- Lambda and Confidence Interval: - It determines the type and extent of transformation applied to the data.
- The above image shows Lambda values and confidence intervals. This lambda value converts the distribution of data into a normal distribution.
The above graphs show the distribution before and after the application of Box-Cox transformation. It is clearly seen the that data is more normally distributed after the application of Box-cox transformation.
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