# What is Mallet?
Mallet (MAchine Learning for LanguagE Toolkit) is an open-source Java-based software package designed for natural language processing (NLP) and text classification tasks. Developed by the University of Massachusetts Amherst, it provides efficient tools for document classification, sequence tagging, topic modeling, and other machine learning applications in text analysis.
## Key Features
1. Topic Modeling – Mallet includes implementations of algorithms like Latent Dirichlet Allocation (LDA) for discovering hidden topics in large text collections.
2. Text Classification – Supports Naive Bayes, Maximum Entropy, and other classifiers for categorizing documents.
3. Sequence Tagging – Useful for tasks like named entity recognition (NER) using Conditional Random Fields (CRFs).
4. Data Processing – Offers tools for tokenization, stopword removal, and feature extraction.
## Why Use Mallet?
Mallet is widely used in academia and industry due to its robustness, scalability, and ease of integration with Java applications. It is particularly popular for research in computational linguistics and text mining.
For more details, visit the [official Mallet website](http://mallet.cs.umass.edu/).