Is feature normalization important for numerical data?
Hello everyone!!! 🖥️📊🔢 Today's Q&A in Data Science!! 📚📖📝 "Is feature normalization important for numerical data?" 1. What is Numerical Data? Numerical data is divided into discrete numeric data that can be divided, such as dice scales and population counts, and continuous numeric data that cannot be divided, such as height and weight. 2. What is feature normalization? Feature normalization is a method of scaling the range of data to a specific interval. Normalization is done to reduce the difficulty of calculations, for example, when the units are different, such as dollars, won, or yen. Representative normalization techniques include min-max scaling using maximum and minimum values, z-normalization using the mean and variance of the data distribution, log normalization, and winsorizing, which excludes the top and bottom n% outliers from min-max scaling. 3. Is feature normalization important for numerical data? In conclusion, feature normalization is important...