Potts Clustering with Complete Shrinkage
Project description
Potts Complete Shrinkage
Potts Clustering with Complete Shrinkage
Installation
Install using pip
pip install pottscompleteshrinkage
Requirements
- Python 3.6 or greater
- numpy
- pandas
Usage
Import the Potts Complete Shrinkage module
import pottsshrinkage.completeshrinkage as PCS
Choose the number of colors
q = 20
Compute Initial Potts Clusters as a first Random Partition (with Potts Model)
InitialPottsClusters = PCS.InitialPottsConfiguration(Train_PottsData_demo, q, Kernel='Mercer')
Choose your temperature (T) level
T = 1000
Set the bandwidth of the model
sigma = 1
Set the Number of Random_Partitions you want to simulate
Number_of_Random_Partitions = 3
Set your initial (random) Potts partition as computed above
Initial_Partition = InitialPottsClusters
Set the Minimum Size desired for each partition generated
MinClusterSize = 5
Run your Potts Complete Shrinkage Model to simulate the Randomly Shrunk Potts Partitions. Partitions_Sets is a dictionary that can be saved with pickle package.
Partitions_Sets,Spin_Configuration_Sets = PCS.Potts_Random_Partition (Train_PottsData_demo, T, sigma, Number_of_Random_Partitions, MinClusterSize, Initial_Partition, Kernel='Mercer')
Pypi Project Page
https://pypi.org/project/pottscompleteshrinkage/1.0.0/
Execution Code Pipeline in Jupyter Notebook
https://github.com/kgalahassa/pottscompleteshrinkage-notebook
Project details
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