Adatkiválasztás
Adatkiválasztás, often translated as data selection or feature selection in English, refers to the process of identifying and selecting a subset of relevant features from a larger dataset. This process is crucial in various fields, including machine learning, data mining, and statistical analysis, as it aims to improve model performance, reduce computational complexity, and enhance interpretability.
The primary goal of datakiválasztás is to remove irrelevant, redundant, or noisy features that might negatively
Several methods exist for datakiválasztás, broadly categorized into filter, wrapper, and embedded methods. Filter methods evaluate