How to transform data to normal distribution | homoscedasticity
#homoscedasticity #variabletransformation #normal distribution
git link : https://github.com/coders-digest/feat...
How to transform data to normal distribution -
homoscedasticity and variable transformation - Some of the machine learning models like linear and logistic regression assume that the features are normally distributed also known as homoscedasticity also known as normal distribution .
Homoscedasticity describes a situation in which the error term (that is, the “noise” or random disturbance in the relationship between the independent variables and the dependent variable) is the same across all values of the independent variables.
we find that very often features are not normally distributed, and that is the whole reason why we need to transform them.
so the next question arise , what are the possible transformations to achieve data transformation and normality testing
The most commonly used methods to transform variables are:
Logarithmic transformation
Reciprocal/inverse transformation
Square root transformation
box cox transformation
Yeo Johnson transformation
exponential transformation
