Testing Unsupervised Machine Learning Algorithms

All over the Internet, I can see applications of supervised and unsupervised Machine Learning Algorithms but no one is talking about maintaining the quality of machine learning apps. The recent analysis on how to test unsupervised machine learning algorithms brought up these points:

1) Cross-validation Testing: Dataset is divided into equal folds(parts) and all folds except the one are used as training dataset and later is used as test dataset

Few more options around using test and training dataset.
Are there more effective ways of testing unsupervised ML algorithms where the output is uncertain?