cross validation

In machine learning (ML), cross validation is a method in which the data scientists perform an evaluation of an ML model's performance on unlabelled data, i.e. data which the ML model has not seen before. In the method of cross validation, the data which is available in the dataset is split into multiple subsets. One ... Read more


In machine learning, a hyperparameter is a parameter external to the ML model, which controls the learning process. A hyperparameter is not related to the internal workings of the ML model but rather indirectly affects the model's internal parameters via the ML model training (fitting) process. The usage of hyperparameter types vary depending on the ... Read more