What is a Boltzmann Machine?
Boltzmann Machines
Keeping this thought in mind, let’s look at a Boltzmann Machine:
Some key features stand out immediately:
- Each node is connected to all other nodes.
- There is no single output in the machine, only hidden units and visible units, where the visible units represent the data. This model tries to understand the distribution of the data and recreate the data based on that distribution.
Even with only a few nodes, there are too many connections in a Boltzmann Machine to make efficient computations. To resolve this, researchers came up with Restricted Boltzmann Machines (RBMs) in which the visible and hidden nodes are independent among themselves.
The Boltzmann Machine was invented in the mid 1980s, and happens to be a part of the Artificial Neural Networks(ANN). Boltzmann Machines consist of a recurrent structure and help in providing optimised solutions to a problem.
The main purpose of Boltzmann Machine is to optimize the solution of a problem. It is the work of Boltzmann Machine to optimize the weights and quantity related to that particular problem. They consist of either of the two states, i.e. 0 and 1.