Data Transformation in R – How to do boxcox transformation in R

Hits: 44

Data Transformation in R – How to do boxcox transformation in R

Data transformation is a technique used to change the distribution of a dataset to make it more amenable to certain statistical techniques. One such technique is the Box-Cox transformation, which is used to stabilize the variance of the data and make it more normal-like.

The Box-Cox transformation is a family of power transformations that can be applied to a variable to make it more normal. The function is defined as:

y = (x^λ – 1) / λ

Where x is the variable to be transformed, λ is a parameter that controls the shape of the transformation, and y is the transformed variable.

In R, the boxcox() function from the MASS package can be used to perform a Box-Cox transformation. The function takes two arguments: the variable to be transformed and the value of λ. The function returns a list containing the transformed variable and the optimal value of λ.

The optimal value of λ is found using maximum likelihood estimation. It can be set to a specific value or can be estimated from the data.

It’s important to note that when λ = 0, the Box-Cox transformation becomes a log transformation. This can be useful when the data has a positive skew and contains zero or negative values.

In summary, Data transformation is a technique used to change the distribution of a dataset to make it more amenable to certain statistical techniques. One such technique is the Box-Cox transformation, which is used to stabilize the variance of the data and make it more normal-like. The Box-Cox transformation is a family of power transformations that can be applied to a variable to make it more normal. In R, the boxcox() function from the MASS package can be used to perform a Box-Cox transformation, the function takes two arguments: the variable to be transformed and the value of λ. The function returns a list containing the transformed variable and the optimal value of λ. The optimal value of λ is found using maximum likelihood estimation. It can be set to a specific value or can be estimated from the data, and when λ = 0, the Box-Cox transformation becomes a log transformation.

 

In this Applied Machine Learning & Data Science Recipe (Jupyter Notebook), the reader will find the practical use of applied machine learning and data science in R programming: Data Transformation in R – How to do boxcox transformation in R.



Data Transformation in R – How to do boxcox transformation in R

Personal Career & Learning Guide for Data Analyst, Data Engineer and Data Scientist

Applied Machine Learning & Data Science Projects and Coding Recipes for Beginners

A list of FREE programming examples together with eTutorials & eBooks @ SETScholars

95% Discount on “Projects & Recipes, tutorials, ebooks”

Projects and Coding Recipes, eTutorials and eBooks: The best All-in-One resources for Data Analyst, Data Scientist, Machine Learning Engineer and Software Developer

Topics included: Classification, Clustering, Regression, Forecasting, Algorithms, Data Structures, Data Analytics & Data Science, Deep Learning, Machine Learning, Programming Languages and Software Tools & Packages.
(Discount is valid for limited time only)

Disclaimer: The information and code presented within this recipe/tutorial is only for educational and coaching purposes for beginners and developers. Anyone can practice and apply the recipe/tutorial presented here, but the reader is taking full responsibility for his/her actions. The author (content curator) of this recipe (code / program) has made every effort to ensure the accuracy of the information was correct at time of publication. The author (content curator) does not assume and hereby disclaims any liability to any party for any loss, damage, or disruption caused by errors or omissions, whether such errors or omissions result from accident, negligence, or any other cause. The information presented here could also be found in public knowledge domains.

Learn by Coding: v-Tutorials on Applied Machine Learning and Data Science for Beginners

There are 2000+ End-to-End Python & R Notebooks are available to build Professional Portfolio as a Data Scientist and/or Machine Learning Specialist. All Notebooks are only $19.95. We would like to request you to have a look at the website for FREE the end-to-end notebooks, and then decide whether you would like to purchase or not.

Please do not waste your valuable time by watching videos, rather use end-to-end (Python and R) recipes from Professional Data Scientists to practice coding, and land the most demandable jobs in the fields of Predictive analytics & AI (Machine Learning and Data Science).

The objective is to guide the developers & analysts to “Learn how to Code” for Applied AI using end-to-end coding solutions, and unlock the world of opportunities!

https://setscholars.net/data-transformation-in-r-how-to-do-center-transformation-in-r/

Data Transformation in R – How to do pca transformation in R

Data Transformation in R – How to standardize Data in R