Testaufteilung
Testaufteilung, also known as test splitting or test partitioning, is a technique used in software development and machine learning to divide a dataset into distinct subsets for the purpose of evaluating the performance of a model or system. The most common approach involves splitting the data into at least two sets: a training set and a testing set.
The training set is used to train the model, allowing it to learn patterns and relationships within
In some cases, a third set, known as a validation set, is also employed. The validation set
The specific ratios for splitting data into training, validation, and testing sets can vary depending on the