Normalize
bestNormalize, Arcsinh Transformation, Box-Cox Normalization, Lambert W x F Normalization,log Transformation, sqrt Normalization, Yeo-Johnson Normalization, Transform Normalize
Common
Input Data
Inputs | |
Target Data | Input data |
Output Name | Name of the output after normalization |
Normalize info | Short description of the work. It should not contain spaces. |
sample | Number of samples. 400 by default |
x | Variables to normalize. Only numeric or integer types will show up. Drag the variables from the table and drop them under X. |
Statistic & p_value
The two variables are the result of Shapiro-Wilk test. The null hypothesis of the Shapiro-Wilk test is that the data is normally distributed. If the p-value is greater than the alpha level, the null hypothesis cannot be rejected therefore indicating that the data is normally distributed. The program will run the test again with the given sample number whenever you click the green arrow button.
Transformation Normalize
This task is used to mitigate the influence of the heavy-tailed distributions while preserving the 1-1 nature of the transformation.
Input Data
Inputs | |
Target Data | Input (vector-like) data |
Output Name | Name of the output after Transformation Normalize |
Normalize info | Normalize Info of 'Normalize' task generated before doing 'Transform Normalize' task .
|
How to Use
Use vector-like data as input for the normalization
Use other 'Normalize' tasks such as 'bestNormalize' to normalize the input value
Then, Transform_Normalize can be used.
Workflow Example
R-Flow Task Example Video - Transform Normalize
R Package
Best Normalize: https://cran.r-project.org/web/packages/bestNormalize/index.html
Arcsinh Transformation, Box-Cox Normalization, Lambert W x F Normalization,log Transformation, sqrt Normalization, Yeo-Johnson Normalization: https://cran.r-project.org/web/packages/bestNormalize/vignettes/bestNormalize.html
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