In unsupervised learning the training set is unlabelled, that is it has no markers to indicate a desired grouping or value. Unsupervised learning algorithms look for commonalities to group or infer other properties of the data. This may be used on its own, or be used as the first stage before human labelling or for a subsequent supervised learning method.
Defined on page 88
Used on Chap. 5: page 88; Chap. 6: pages 121, 124; Chap. 8: pages 154, 160, 162, 170; Chap. 9: pages 176, 177, 178, 188, 189, 194, 195, 196; Chap. 10: page 211; Chap. 12: page 278; Chap. 14: page 330; Chap. 16: page 377; Chap. 18: pages 439, 440, 446
Also known as unsupervised, unsupervised algorithm, unsupervised algorithms, unsupervised approach, unsupervised machine learning, unsupervised technique, unsupervised training