{"categories":[{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/9"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/3"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics/3"},{"label":"Bio-Informatics","url":"https://skillfed.io/packages/category/scientific-engineering-bio-informatics"}],"enrichment":{"capability":"Performs fast hierarchical agglomerative clustering from distance matrices or vector data, replacing scipy.cluster.hierarchy functions with optimized C++ implementations.","skillfed_tags":["clustering","hierarchical-methods","performance-optimized"],"use_cases":["Cluster datasets faster than scipy.cluster.hierarchy when hierarchical agglomerative methods are needed.","Generate dendrograms from distance matrices or vector data for exploratory data analysis.","Port MATLAB clustering code to Python with minimal API changes.","Memory-efficient clustering of vector data via the linkage_vector function.","Perform bioinformatics clustering where hierarchical methods are standard."],"what_it_does":"fastcluster is a Python library for hierarchical agglomerative clustering that reimplements scipy.cluster.hierarchy functions (linkage, single, complete, average, weighted, centroid, median, ward) with faster C++ algorithms. It accepts either distance matrices or raw vector data and generates hierarchical clusters represented as dendrograms. The interface mirrors MATLAB's Statistics Toolbox to ease code porting.\n\nThe package is a stable, mature tool designed as a drop-in replacement for scipy when speed matters. It depends only on numpy and requires Python 3 or later. Recent versions track scipy's distance function definitions\u2014notably the Jaccard and Yule distance changes in version 1.3.0\u2014so version pairing with scipy is recommended to avoid inconsistencies.","worth_installing":"Yes, if you need hierarchical clustering and scipy's performance is insufficient. The package is stable, has no known vulnerabilities, and offers a straightforward scipy-compatible API. The aging maintenance status is not a concern given the author's stated design philosophy (infrequent updates by design). Verify scipy version compatibility using the documented pairings to avoid distance function mismatches."},"id":"fastcluster","links":{"html":"https://skillfed.io/packages/fastcluster","md":"https://skillfed.io/packages/fastcluster.md","pypi":"https://pypi.org/project/fastcluster/"},"maintenance":{"status":"aging"},"meta":{"latest_release":"2025-05-06","license_spdx":null,"license_treatment":"copyleft","name":"fastcluster","python_support":"supports_current","summary":"Fast hierarchical clustering routines for R and Python."},"popularity":{"monthly_downloads":116614,"position":12198,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.3.0"}