piirteistyminen
Piirteistyminen is a Finnish term that translates to "featurization" or "feature extraction" in English, particularly in the context of data science and machine learning. It refers to the process of selecting, transforming, and creating relevant features from raw data to improve the performance and interpretability of machine learning models. Raw data, such as images, text, or numerical datasets, often contains a large amount of information, not all of which is directly useful for a given task. Piirteistyminen aims to distill this information into a more manageable and informative set of characteristics, known as features.
The goal of piirteistyminen is to create a feature representation that highlights the important aspects of