Normalization

A harmonizing process, like tuning instruments in an orchestra, normalization adjusts the scale of numerical variables in a dataset, bringing them into a common range, thereby enabling more accurate comparisons and improving the performance of machine learning models.

Example

Imagine a dataset containing information about houses, including variables such as square footage (ranging from 500 to 5,000) and the number of rooms (ranging from 1 to 10). The difference in scale between these variables might cause a machine learning model to give more weight to the square footage variable, potentially leading to biased or inaccurate predictions. By normalizing the variables, such as scaling their values between 0 and 1, the model can more accurately assess the importance of each variable and make better predictions.