When taking measurements of real-world objects, we can often get features in different ranges. For instance, if we measure the qualities of an animal, we might have several features, as follows:
- Number of legs: This is between the range of 0-8 for most animals, while some have more! more! more!
- Weight: This is between the ranges of only a few micrograms, all the way to a blue whale with a weight of 190,000 kilograms!
- Number of hearts: This can be between zero to five, in the case of the earthworm.
For a mathematical-based algorithm to compare each of these features, the differences in the scale, range, and units can be difficult to interpret. If we used the above features in many algorithms, the weight would probably be the most influential feature due to only the larger numbers and not anything to do with the actual effectiveness of the feature.
One of the possible strategies normalizes the features so that they all have the same range, or the values are turned into categories...