Tests are the only way to estimate the quality of a machine learning algorithm in practice. In order to prove your algorithm is usable, you need to design good tests. To design test you should collect the data and split them into the train set and the test set.
- Repeated random sub-sampling validation
- K-fold cross-validation
- Leave-one-out cross-validation