A robust EM clustering algorithm for Gaussian mixture models
Project description
A Robust EM Clustering Algorithm for Gaussian Mixture Models
Description
Python implementation of Robust EM Clustering for Gaussian Mixture Models[1]. (Click here to view the paper for more detail.)
-
robustGMM.robustGMM
Scikit-learn API style for Robust GMM
-
robustGMM.generator
Generator for synthetic data from mixture of gaussian.
For more detail to use, see the example below or paper_example.py
-
Reference
MS Yang, A robust EM clustering algorithm for gaussian mixture models, Pattern Recognit., 45 (2012), pp. 3950-3961
---
Install
-
Install from PyPI
pip install robustGMM
-
Install from Github
pip install git+https://github.com/HongJea-Park/robust_EM_for_gmm.git
---
Example
All examples are conducted to compare with the experimental results of the paper.
# For more detail, refer ./test/paper_example.py
import numpy as np
from robustGMM import RobustGMM
from robustGMM import Generator_Multivariate_Normal
# Generate data from 2 multivariate normal distribution with fixed random seed
np.random.seed(0)
real_means = np.array([[.0, .0], [20, .0]])
real_covs = np.array([[[1, .0], [.0, 1]],
[[9, .0], [.0, 9]]])
mix_prob = np.array([.5, .5])
generator = Generator_Multivariate_Normal(means=real_means,
covs=real_covs,
mix_prob=mix_prob)
X = generator.get_sample(800)
# GMM using robust EM Algorithm
rgmm = RobustGMM()
rgmm.fit(X)
Figures for each examples in paper
-
Example 1
-
Example 2
-
Example 3
-
Example 4
-
Example 5
-
Example 6
-
Example 7
-
Computational time cost
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
robustgmm-1.0.0.tar.gz
(6.2 kB
view hashes)
Built Distribution
Close
Hashes for robustgmm-1.0.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b45362e3e02afd6b26e40c65268d324fdb677f79088f9eb6f3ae017ec80974c4 |
|
MD5 | e8e4670172e89a71c7d4f9fbc77a2901 |
|
BLAKE2b-256 | 2f18b85c80ae7d6989f9fa6f5feec11a7411282f9ed191e72a9b500718abb6de |