Skip to main content

Python AutoML library for clustering tasks

Project description

clustermatic

clustermatic

clustermatic is a Python library designed to accelerate clustering tasks using scikit-learn. It serves as a quick tool for selecting the optimal clustering algorithm and its hyperparameters, providing visualizations and metrics for comparison.

Features

  • Clustering Algorithms: Analyzes six clustering algorithms from scikit-learn:
    • KMeans
    • DBSCAN
    • MiniBatchKMeans
    • AgglomerativeClustering
    • OPTICS
    • SpectralClustering
  • Optimization Methods: Includes Bayesian optimization and random search for hyperparameter tuning.
  • Evaluation Metrics: Supports evaluation with silhouette, calinski_harabasz, and davies_bouldin scores.
  • Report Generation: Generates reports in HTML format after optimization.

Installation

To install clustermatic, use pip:

pip install clustermatic

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

clustermatic-0.0.1.tar.gz (49.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

clustermatic-0.0.1-py3-none-any.whl (49.4 kB view details)

Uploaded Python 3

File details

Details for the file clustermatic-0.0.1.tar.gz.

File metadata

  • Download URL: clustermatic-0.0.1.tar.gz
  • Upload date:
  • Size: 49.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.7

File hashes

Hashes for clustermatic-0.0.1.tar.gz
Algorithm Hash digest
SHA256 bf9762bba6a0bdc7d8f8926512c51a96edaefee580d825e1248a4f4eea9494f7
MD5 49fc3a9f50dace994d4f184d3869c5be
BLAKE2b-256 3a6fd2f0211178a40ced120b213a788d3c96d3c8a5b730459cefbaa32239e002

See more details on using hashes here.

File details

Details for the file clustermatic-0.0.1-py3-none-any.whl.

File metadata

  • Download URL: clustermatic-0.0.1-py3-none-any.whl
  • Upload date:
  • Size: 49.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.10.7

File hashes

Hashes for clustermatic-0.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 8ac65cf80bf0dbd03818dbffc977c9509a0446400295bc3aa3b8957e9eab7e27
MD5 8a28b3476a75e70b7e267541a6193005
BLAKE2b-256 e73584e95001e1752635438f09927d1bb1fa2d22aa2500e2989cd24c9be14003

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page