mclustpy is a Python function for clustering data using the Mclust algorithm from the R package mclust. The function takes a 2D numpy array of data and returns a dictionary containing various output values computed by the Mclust algorithm.
mclustpy requires the following dependencies:
- numpy
- rpy2
To install mclustpy, you can use pip:
pip install mclustpy
from mclustpy import mclustpy
import numpy as np
data = np.random.rand(1000, 10)
data.shape
res = mclustpy(data, G=9, modelNames='EEE', random_seed=2020)- data: a 2D numpy array of data to be clustered.
- G: an integer specifying the maximum number of mixture components to be considered (default is 9).
- modelNames: a string specifying the model types to be considered (default is 'EEE').
- random_seed: an integer specifying the random seed for reproducibility (default is 2020).
- call: the function call used to run the Mclust algorithm.
- data: the input data as an R matrix.
- modelName: the model name(s) selected by the algorithm.
- n: the number of observations in the data.
- d: the number of variables in the data.
- G: the number of mixture components selected by the algorithm.
- BIC: the Bayesian Information Criterion (BIC) value for the selected model.
- loglik: the log-likelihood of the selected model.
- df: the number of degrees of freedom in the selected model.
- bic: the BIC value for each model considered.
- icl: the Integrated Completed Likelihood (ICL) value for each model considered.
- hypvol: the hypervolume of the cluster tree for each model considered.
- parameters: the estimated parameters for each component in the selected model.
- z: the posterior probabilities of assignment to each component for each observation.
- classification: the classification of each observation under the selected model.
- uncertainty: a measure of uncertainty in the classification of each observation.
For more info take a look at the original mclust page