**2.3 Deep belief network (DBN)**

DBN is a probabilistic unsupervised deep learning algorithm. It has many layers of hidden variables. To solve the more complex problems, it needs more hidden layers; each layer is a special statistical relation with the other layer. DBN can learn probabilistically; after learning, BDN needs training under supervisor to perform classification. The DBN is used to recognize clusters and generates images, video sequences, and motion-capture data (**Figure 4**).

## **2.4 Boltzmann machine (BM)**

The BM is a network that is a uniformly attached, neuron-like unit, which is responsible for taking decisions stochastically about whether to be off or on. Computational problems are solved through BM like search, optimization, and learning problem. Many features are uncovered in learning algorithm that shows

very complex behavior in training dataset. Boltzmann machine is used for classification and dimensionality reduction.
