Demystifying Feature Scaling
Feature scaling is an important technique in Machine Learning and it is one of the most important steps during the preprocessing of data before creating a machine learning model. This can make a difference between a weak machine learning model and a ...
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This is an interesting topic. It's essentially a way to compare 'incomparible' dimensions.
I.e. you might have the top speed of a car, the weight and the horse power of the engine, and you want to determine if it's similar to another car. But if car A and B differ in weight by 100kg and car A has 2 more horse power than C, then is A more similar to B or to C?
Standardizing is an approach that let's you not think about the conversion factor from kgs-of-car to hps-of-engine. It's not always the best approach, but it's usually the easiest, and maybe less likely to have human bias.
Also many non-linear things like neural networks (assuming a non-linear activation function).