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Feature transformation is a mathematical transformation in which we apply a mathematical formula to a particular column (feature) and transform the values, which are useful for our further analysis. It is a technique by which we can boost our model performance.

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Feature Transformation

Description

Feature transformation refers to the process of altering the original features or variables in a dataset to create new representations that might be more suitable for analysis or modeling. This process can involve various techniques, such as scaling, normalization, encoding categorical variables, creating new features through mathematical operations, and more.

The Process of Feature Transformation:
1.Normalization
2.Standardization
3.Logarithm(log) Transformation
4.Robust Scaler
5.Max Absolute Scaler

About

Feature transformation is a mathematical transformation in which we apply a mathematical formula to a particular column (feature) and transform the values, which are useful for our further analysis. It is a technique by which we can boost our model performance.

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