We will then move on to the Grid Search algorithm and see how it can be used to automatically select the best parameters for an algorithm. We will first study what cross validation is, why it is necessary, and how to perform it via Python’s Scikit-Learn library. In this article we will explore these two factors in detail. One such factor is the performance on cross validation set and another other factor is the choice of parameters for an algorithm. There are several factors that can help you determine which algorithm performance best.
However, evaluating the performance of algorithm is not always a straight forward task. A typical machine learning process involves training different models on the dataset and selecting the one with best performance.
