Distance-based methods, whether for dimensionality reduction or clustering, are susceptible to feature scales. Therefore, it is advisable to apply appropriate normalization techniques before training these models. Another commonly used method for data rescaling is min -max scaling, which adjusts data to a fixed range, typically [0, 1]. This is achieved by subtracting the minimum value from all data points and then dividing it by the range, which is the difference between the minimum and maximum values.