esikäsitellyiltä
Esikäsitelty is a term used in the context of data processing and machine learning to describe data that has undergone preliminary processing before being used for further analysis or modeling. This preprocessing step is crucial for improving the quality and effectiveness of the subsequent analysis. The primary goals of esikäsitelty data are to clean the data, reduce noise, and prepare it in a format that is suitable for the specific algorithms or models being used.
Common preprocessing techniques include data cleaning, which involves handling missing values, removing duplicates, and correcting errors.
Esikäsitelty data can significantly enhance the performance of machine learning models by ensuring that the input
In summary, esikäsitelty refers to data that has been preprocessed to improve its quality and suitability for