Understanding advanced data preprocessing techniques in MATLAB
After introducing data preprocessing techniques, in this section, we will analyze some data preprocessing techniques in MATLAB with practical examples. We will talk about min-max scaling and z-score standardization, which are two common techniques used to normalize data in ML. Both techniques aim to rescale numerical data to a common scale, making it easier for ML algorithms to learn from the data.
Data normalization for feature scaling
Data normalization is a preprocessing step used to scale and standardize data to a common range or distribution. It aims to bring different features or variables to a comparable scale, ensuring that no single feature dominates the analysis due to its larger magnitude. Normalizing data can also help improve the performance of certain ML algorithms. There are various techniques for data normalization, including the following:
- Min-Max scaling: This method scales the data to a...
