PSOClustering VS kmodes

Compare PSOClustering vs kmodes and see what are their differences.

PSOClustering

This is an implementation of clustering IRIS dataset with particle swarm optimization(PSO) (by NiloofarShahbaz)

kmodes

Python implementations of the k-modes and k-prototypes clustering algorithms, for clustering categorical data (by nicodv)
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PSOClustering kmodes
1 2
14 1,219
- -
0.0 4.2
almost 2 years ago 5 days ago
Python Python
Apache License 2.0 MIT License
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PSOClustering

Posts with mentions or reviews of PSOClustering. We have used some of these posts to build our list of alternatives and similar projects.
  • Need help understanding Particle Swarm Optimization
    1 project | /r/learnmachinelearning | 11 May 2022
    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.

kmodes

Posts with mentions or reviews of kmodes. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing PSOClustering and kmodes you can also consider the following projects:

PSO-cont-sched - Made for a college project, this Java program attempts to demonstrate how PSO might be used to solve container scheduling problems.

yellowbrick - Visual analysis and diagnostic tools to facilitate machine learning model selection.

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)

best-of-ml-python - 🏆 A ranked list of awesome machine learning Python libraries. Updated weekly.

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.

data-science-ipython-notebooks - Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

fuzzy-c-means - A simple python implementation of Fuzzy C-means algorithm.

Dask - Parallel computing with task scheduling