Test set
Test sets play an essential role in machine learning, serving as the benchmark for evaluating how well a model can perform on new, unseen data. This impartial assessment is crucial for ensuring the mo...
Type I error
Type I error is a concept that plays a crucial role in hypothesis testing, significantly affecting how researchers interpret findings. Often referred to as a false-positive error, it can lead to the i...
Validation set
A validation set is a critical element in the machine learning process, particularly for those working within the realms of supervised learning. It helps in refining model parameters through systemati...
