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Feature Scaling (i2tutorials)

What is Feature Scaling?

Feature Scaling or Standardization: It is a step of Data Preprocessing which is applied to independent variables or features of data. It helps to normalize the data within a certain range. It also helps in speeding up the calculations in an algorithm.

Dataset consists of features that highly differ in magnitudes, units, and range. Normalization should be performed when the scale of a feature is irrelevant or misleading and not should Normalize when the scale is meaningful.

The algorithms which use Euclidean Distance measure are sensitive to Magnitudes. Here feature scaling helps to weigh all the features equally.

If a feature in the dataset is large in scale compared to others then in algorithms where Euclidean distance is measured this large scaled feature becomes dominating and needs to be normalized.

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