Is it possible to reuse training sets iteratively and what impact does that have on the performance of the trained model?
Friday, 01 September 2023
by Willem Kok
Iteratively reusing training sets in machine learning is a common practice that can have a significant impact on the performance of the trained model. By repeatedly using the same training data, the model can learn from its mistakes and improve its predictive capabilities. However, it is essential to understand the potential advantages and disadvantages of
- Published in Artificial Intelligence, EITC/AI/GCML Google Cloud Machine Learning, First steps in Machine Learning, The 7 steps of machine learning
Tagged under:
Artificial Intelligence, Concept Drift, Machine Learning, Model Performance, Overfitting, Training Sets