Eiginleikaútdráttur
Eiginleikaútdráttur, a term originating from Icelandic, translates to "feature extraction" in English. It is a fundamental concept in machine learning and data science, referring to the process of transforming raw data into a set of informative features that can be effectively used by algorithms to learn and make predictions. The goal of feature extraction is to reduce the dimensionality of the data while retaining as much of the relevant information as possible, making the learning process more efficient and often improving model performance.
Raw data, such as images, text, or sensor readings, is often too complex or contains too much
The specific techniques used for feature extraction vary widely depending on the type of data and the