Affinity Propagation - Flow Chart
Main Process:
Input data in the form of a matrix or dataset.
Set the parameters of the algorithm such as damping factor, preference value, and maximum number of iterations.
Initialize exemplars and responsibility matrices.
Compute the availability matrix.
Update the responsibility and availability matrices.
Repeat steps 4-5 until convergence or maximum number of iterations is reached.
Assign data points to exemplars.
Display the scatter plot of the data points with different colours for exemplars.
Display the messages being sent between points.
Display the decision-making process of the algorithm.
Inputs:
Data in the form of a matrix or dataset.
Parameters such as damping factor, preference value, and maximum number of iterations.
Outputs:
Scatter plot of the data points with different colours for exemplars.
Display of messages being sent between points.
Display of decision-making process of the algorithm.
Decision Points:
Check if the number of iterations has reached the maximum limit.
Check if the responsibility and availability matrices have converged.
Actions:
Initialize exemplars and responsibility matrices.
Compute the availability matrix.
Update the responsibility and availability matrices.
Assign data points to exemplars.
Display the scatter plot of the data points with different colours for exemplars.
Display the messages being sent between points.
Display the decision-making process of the algorithm.
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