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networkx / networkx

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cdlib

GiulioRossetti / cdlib

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ZeroDevisionError in Expectation Maximization Community Algorithm

5
OUStudent
OUStudent commented Nov 24, 2021

Trying to use em function to find communities in my undirected networkx Graph.

Line 31 in algorithms\internal\em.py there is a
q[i][g] /= norm, which throws a division by zero error. Looking at the source code of the e_step function:

    def e_step(self, q):
        for i in range(self.n):
            q.append([])
            norm = 0.0
            for g in range(self.k):
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dcmocanu / sparse-evolutionary-artificial-neural-networks

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Always sparse. Never dense. But never say never. A Sparse Training repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).

deep-neural-networks sparsity deep-learning scalability randomization neuroevolution deep-learning-algorithms classification evolutionary-algorithms artificial-neural-networks restricted-boltzmann-machine complex-networks deep-learning-papers multi-layer-perceptron generative-models sparse-neural-networks scalable-deep-learning sparse-training sparse-evolutionary-training adaptive-sparse-connectivity
  • Updated Jul 21, 2021
  • Python

lgaalves / AppliedMathSchoolLectures

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Lectures on "crime and political corruption analysis using data mining, machine learning and complex networks" at the School of Applied Mathematics in the Institute of Mathematics and Computer Science at University of São Paulo

python data-science machine-learning data-mining big-data social-networks scikit-learn jupyter-notebook community-detection networkx web-scraping complex-networks igraph crime-prediction corruption-networks crimonology quantitative-criminology
  • Updated Jul 7, 2019
  • Jupyter Notebook

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