Normalizing data

Data normalization is a crucial preprocessing step in machine learning. In general, data normalization is a process that transforms multiscaled data to the same scale. Feature values in a dataset can have very different scales—for example, the height can be given in centimeters with small values, but the income can have large-value amounts. This fact has a significant impact on many machine learning algorithms. For example, if some feature values differ from values of other features several times, then this feature will dominate over others in classification algorithms based on the Euclidean distance. Some algorithms have a strong requirement for normalization of input data; an example of such an algorithm is the Support Vector Machine (SVM) algorithm. Neural networks also usually require normalized input data. Also, data normalization has an impact on...