clus
PSOClustering
clus | PSOClustering | |
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1 | 1 | |
9 | 14 | |
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2.9 | 0.0 | |
7 months ago | almost 2 years ago | |
Python | Python | |
- | Apache License 2.0 |
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clus
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Interview Practice: Coding K-Means Clustering using Python and NumPy
Nice work ! I also worked on an implementation with only matrix operations and without copying matrix between computations a long time ago. I wanted to compare differents algorithms on a huge dataset. You can check it out if you are interested. And if you want to spice things up a bit, you have the fuzzy-c-means algorithm which is not that complicated compared to k-means and can give more information about your clustering.
PSOClustering
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Need help understanding Particle Swarm Optimization
I apologize for the very basic question, but I have been having trouble understanding this. So I get PSO in terms of finding a maximum or minimum, given a function. But where I am lost is applying the algorithm to data sets. The one I am looking at is applying the process to the Iris Flower Dataset.
What are some alternatives?
kmodes - Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data
PSO-cont-sched - Made for a college project, this Java program attempts to demonstrate how PSO might be used to solve container scheduling problems.
scikit-opt - Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing, Ant Colony Optimization Algorithm,Immune Algorithm, Artificial Fish Swarm Algorithm, Differential Evolution and TSP(Traveling salesman)
zoofs - zoofs is a python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.
fuzzy-c-means - A simple python implementation of Fuzzy C-means algorithm.
MinSizeKmeans - A python implementation of KMeans clustering with minimum cluster size constraint (Bradley et al., 2000)
AnnA_Anki_neuronal_Appendix - Using machine learning on your anki collection to enhance the scheduling via semantic clustering and semantic similarity