mixturs

Unofficial implementation of Dirichlet Process Mixture Model Sub-Clusters algorithm.

To use as a library, add the following to your Cargo.toml. Executable builds can be found at https://github.com/EgorDm/mixturs/releases.

[dependencies]
mixturs = "0.1"

Features

Cluster points without knowing the number of clusters in advance
Fastest CPU implementation of the algorithm
Python bindings to cluster numpy data
Command line tool for generating segmented images from JPG/PNG input files

Examples

Rust Examples:

// Load data into a col major matrix
let x: DMatrix<f64> = ...;

// Set model options
let mut model_options = ModelOptions::<NIW>::default(dim);
model_options.alpha = 100.0;
model_options.outlier = None;

// Set fit options
let mut fit_options = FitOptions::default();
fit_options.init_clusters = 1;

// Configure callbacks
let mut callback = MonitoringCallback::from_data(
    EvalData::from_sample(&x, Some(&y), 1000)
);
callback.add_metric(AIC);
callback.add_callback(PlotCallback::new(
    3,
    "examples/data/plot/synthetic_2d".into(),
    EvalData::from_sample(&x, None, 1000)
));
callback.set_verbose(true);

// Fit the model
let mut model = Model::from_options(model_options);
model.fit(
    x.clone_owned(),
    &fit_options,
    Some(callback),
);

Python Examples:

import numpy as np
from mixtupy import *

# Load data
x = ...

# Configure model
mo = ModelOptions(2)
model = Model(mo)

# Fit model
fo = FitOptions()
fo.iters = 200
fo.aic = True
model.fit(x, fo, y=y)

# Predict data point labels
probs, labels = model.predict(x)

# Extract cluster parameters
print(model.cluster_weights())
print(model.cluster_params())

Reference

[1] J. Chang and J. W. Fisher III, “Parallel Sampling of DP Mixture Models using Sub-Cluster Splits,” in Advances in Neural Information Processing Systems, 2013.