- The former belongs to supervised learning and the latter belongs to unsupervised learning
- The distinct difference between supervised learning and unsupervised learning lies in whether the example consists of the pre - processed output value
- Decision theory , statistical classification , maximum likelihood and bayesian estimation , non - parametric methods , unsupervised learning and clustering
- Due to its unsupervised learning ability , clustering has been widely used in numerous applications , such as pattern recognition , image processing , market research and so on
In machine learning, unsupervised learning refers to the problem of trying to find hidden structure in unlabeled data. Since the examples given to the learner are unlabeled, there is no error or reward signal to evaluate a potential solution.