getting empty p_micro_cluster_centers when trying the algorithm with less n_samples (10, 50, 100, 300 ...)

[onofricamila]

As the title says, I'm struggling trying to decode **why I am getting empty p_micro_cluster_centers when running Test.py setting n_samples to a smaller number **. Any help will be appreciated.

I don't know why but there are not any issues of the kind if the data set you use has much more elements. I tried the algorithm with 500 n_samples and it worked fine.

IMPORTANT: there seems to be a problem in the _partial_fit method when it comes to generate p_micro_clusters ... I think it has to do with the if statement but I do not know what to do about it:

def _partial_fit(self, sample, weight):
     self._merging(sample, weight)
     if self.t % self.tp == 0:
         self.p_micro_clusters = [p_micro_cluster for p_micro_cluster
                                  in self.p_micro_clusters if
                                  p_micro_cluster.weight() >= self.beta *
                                  self.mu]
         Xis = [((self._decay_function(self.t - o_micro_cluster.creation_time
                                       + self.tp) - 1) /
                 (self._decay_function(self.tp) - 1)) for o_micro_cluster in
                self.o_micro_clusters]
         self.o_micro_clusters = [o_micro_cluster for Xi, o_micro_cluster in
                                  zip(Xis, self.o_micro_clusters) if
                                  o_micro_cluster.weight() >= Xi]
     self.t += 1

Thanks in advance!