Project details for Aleph

Logo Aleph 0.6

by jiria - January 12, 2009, 20:52:12 CET [ Project Homepage BibTeX Download ]

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Description:

Aleph is both a multi-platform machine learning framework aimed at simplicity and performance, and a library of selected state-of-the-art algorithms.

Aleph features:

  • semi-supervised algorithms: graph label propagation, discrete regularization, etc.

  • large-scale linear algorithms: logistic linear regression, stochastic gradient descent linear SVM, etc.

  • wrappers to well-known tools: libsvm, SVMlight, etc.

  • graph-based algorithms: random walks, absorbing random walks, etc.

  • feature selection statistics: infogain, cross entropy, chi-squared, etc.

  • convenience validation utilities: several splitting methods, several scoring functions

  • fast vector and matrix implementations: based on matrix toolkits for java, but with a few optimizations on top of it

  • fast on-the-fly operations over datasets, instances and features: based on the concept of views over those first-class objects in the framework

Most importantly, the framework features a clean design and is therefore easily extensible.

Aleph 0.6 is faster, more stable and better documented than the previous version.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download
URL: Project Homepage
Supported Operating Systems: Agnostic
Data Formats: None
Tags: Large Scale, Graph, Svm, Feature Selection, Multilabel, Machine Learning, Algorithms, Framework, Information Extraction
Archive: download here

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