Observer of EM algorithm for collecting algorithm state on each step. More...
Public Member Functions | |
def | __init__ (self) |
Initializes EM observer. | |
def | __len__ (self) |
def | get_iterations (self) |
def | get_evolution_means (self) |
def | get_evolution_covariances (self) |
def | get_evolution_clusters (self) |
def | notify (self, means, covariances, clusters) |
This method is used by the algorithm to notify observer about changes where the algorithm should provide new values: means, covariances and allocated clusters. More... | |
Observer of EM algorithm for collecting algorithm state on each step.
It can be used to obtain whole picture about clustering process of EM algorithm. Allocated clusters, means and covariances are stored in observer on each step. Here an example of usage:
def pyclustering.cluster.ema.ema_observer.__len__ | ( | self | ) |
def pyclustering.cluster.ema.ema_observer.get_evolution_clusters | ( | self | ) |
def pyclustering.cluster.ema.ema_observer.get_evolution_covariances | ( | self | ) |
def pyclustering.cluster.ema.ema_observer.get_evolution_means | ( | self | ) |
def pyclustering.cluster.ema.ema_observer.get_iterations | ( | self | ) |
def pyclustering.cluster.ema.ema_observer.notify | ( | self, | |
means, | |||
covariances, | |||
clusters | |||
) |
This method is used by the algorithm to notify observer about changes where the algorithm should provide new values: means, covariances and allocated clusters.
[in] | means | (list): Mean of each cluster on currect step. |
[in] | covariances | (list): Covariances of each cluster on current step. |
[in] | clusters | (list): Allocated cluster on current step. |