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

Data Transformation in R – How to do center 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 centering, which is used to make the data zero-mean.

Centering is a simple technique that involves subtracting the mean of the data from each value. This means that the new data will have a mean of zero and the values are measured relative to the mean of the data.

In R, the scale() function can be used to center the data. The scale() function takes a numeric vector or matrix as an argument and returns a centered version of the data. By default, the function centers the data by subtracting the mean from each value, but it also can be centerd by subtracting the median or a custom value.

It’s important to note that centering the data is a necessary step before applying many machine learning and statistical techniques, such as principal component analysis, linear discriminant analysis and regularization.

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 centering, which is used to make the data zero-mean. Centering is a simple technique that involves subtracting the mean of the data from each value. This means that the new data will have a mean of zero and the values are measured relative to the mean of the data. In R, the scale() function can be used to center the data. The scale() function takes a numeric vector or matrix as an argument and returns a centered version of the data. By default, the function centers the data by subtracting the mean from each value, but it also can be centerd by subtracting the median or a custom value. It’s important to note that centering the data is a necessary step before applying many machine learning and statistical techniques.

 

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 center transformation in R.



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

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