what is the process of dividing each feature by its range called in machine learning
Answers
The process of dividing each feature by its range is called feature scaling.
The process feature scaling is used to standardize each variables individually.
The term feature scaling when it comes to data processing is also known as data normalization.
Due to the gradient descent which helps to converge faster is the most important feature of feature scaling.
Machine learning calculations make suspicions about the dataset you are demonstrating.
Regularly, crude information is included characteristics with differing scales. For instance, one quality might be in kilograms and another might be a check. Despite the fact that not required, you can regularly get a lift in execution via cautiously picking techniques to rescale your information.
The way toward partitioning each element by its range is called feature scaling. The procedure include scaling is utilized to institutionalize every factor independently.