# mimno/Mallet

MALLET is a Java-based package for statistical natural language processing, document classification, clustering, topic modeling, information extraction, and other machine learning applications to text.

Repository: https://github.com/mimno/Mallet
Canonical: https://ross.abutalabs.com/products/mallet
Homepage: https://mimno.github.io/Mallet/
Language: Java
License: NOASSERTION
License Family: other
Last push: 2026-08-04T20:21:57+00:00

## Health v2 (maintenance only)
Score: 86/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 96, release rhythm 64, longevity 100
- inputs: {"age_days": 4536, "days_push": 29, "days_rel": 29, "gap_med": 208, "n_releases_24m": 2}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1028, forks 353 (observed 2026-08-28T04:03:17.533994+00:00)

## What it is
MALLET (MAchine Learning for LanguagE Toolkit) is a Java-based package for statistical natural language processing, including document classification, clustering, sequence tagging, and topic modeling. It provides efficient implementations of algorithms such as Naive Bayes, Maximum Entropy, CRFs, and LDA, along with text-processing pipelines and numerical optimization routines.

## Use cases
- train topic models like LDA on large text corpora
- classify documents into categories
- extract named entities from text with CRFs
- cluster unlabeled documents
- convert raw text into feature vectors for machine learning
- run sequence tagging on token streams

## When to choose
- you need mature, sampling-based topic modeling (LDA, Pachinko Allocation, Hierarchical LDA) in Java
- you want classic NLP classification and sequence tagging algorithms on the JVM
- you need efficient text-to-feature pipelines with tokenization and stopword handling

## When to avoid
- you need modern deep-learning or transformer-based NLP models
- your stack is Python-first and you prefer libraries like scikit-learn, Gensim, or spaCy
- you need GPU acceleration for large-scale training

## Facets
- artifact type: library
- maturity: maintenance
- function: machine-learning, nlp, parser, serialization
- domain: machine-learning, text-editors
- platform: jvm, cross-platform, cli
- tags: topic-modeling, lda, document-classification, conditional-random-fields, named-entity-recognition, text-clustering, java, natural-language-processing

## Member repositories
- mimno/Mallet (main) score 86

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:17.533994+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T07:07:47.904575+00:00, confidence not recorded.
  - readme: https://github.com/mimno/Mallet (fetched 2026-08-28T04:03:17.533994+00:00, sha 9d377cafd285)
  - homepage: https://mimno.github.io/Mallet/ (fetched 2026-08-29T13:07:41.408619+00:00, sha 32c4faedb004)
- Data as of 2026-08-30T08:39:29.467469+00:00.