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ankus's Introduction

What is Ankus?

Ankus is an open source data mining / machine learning based MapReduce that supports a variety of advanced algorithms. Apache Mahout have the same goal with us, Mahout complicated convert to Sequence files and configure parameters for a wide variety of machine learning algorithms. But as Ankus can see below, Almost do not need to generate input dataset POV(Point of view) analysis as set up a variety of custom parameters Focus on the pre-processing as normalization dataset

OUR GOAL is, machine learning and data mining library on top of Apache Hadoop using the map/reduce paradigm. And they are an open source project.

Official Release

ankus 0.1 - current stable version
ankus 0.0.1 - first stable version but missing ID3, EM, Content based Similarity modules.

New features of ankus 0.1

  1. Classification - ID3
  2. Clustering - EM
  3. Similarity - Content based Similarity
  4. Recommendation System - Item based recommendation
  5. Recommendation verify module(use RMSE)

Support algorithms

  1. Basic statistics computation for numeric/nominal data (3 methods)
  2. Pre-processing (Normalization, 1 method)
  3. Similarity/correlation analysis for vector type data (3 methods)
  4. Classification/clustering analysis (3 methods)
  5. CF based recommendation analysis (4 methods)

Feautures

  1. Can use without input-file conversion
  2. Support various parameters for algorithms
  3. Support basic statistics and pre-processing methods
  4. Support attributes selection for analysis

Architecture

Alt text

Community

Join community forum!
https://www.facebook.com/groups/openankus

Join facebook page!
https://www.facebook.com/openankus

Only download jar files
https://sourceforge.net/projects/ankus/files/?source=navbar

Demo video
http://youtu.be/gx8i4X82QfQ

License

Apache License 2.0

For Korean

Ankus는 Hadoop MapReduce 기반 환경에서 운용할 수 있는 데이터 마이닝/기계학습 라이브러리 입니다. Apache Mahout과 동일한 목적이나 Mahout은 Sequence 파일로의 변환과 다양한 분석 실험을 위한 파라미터들의 설정이 복잡하고, 접근방법이 어렵습니다. 반면 Ankus는 분석 수행 관점에서 아래와 같이 사용이 가능합니다.

  1. 입력 파일을 별도의 변환 없이 그대로 사용 가능
  2. 다양한 파라미터들을 설정하여 여러 관점에서 분석 가능
  3. 정규화 같은 입력 값의 전처리 등을 수행 할 수 있도록 하는데 더 중점을 둠

빅데이터 환경에서 그동안 어려웠던 마이닝/기계학습 분석을 더욱 쉽게 분석해볼 수 있는 오픈소스 라이브러리입니다.

ankus's People

Contributors

suhyunjeon avatar bramp avatar

Stargazers

Jaedeok Kim avatar Minho Kim avatar Sunmi Kang avatar  avatar UK, Jo avatar  avatar shinjjang avatar  avatar Honam avatar KeunYoung Park avatar Hyunseok Cho avatar CEE avatar Daniel Kyojun Ku avatar Youngwoo Kim avatar Jonghyeon Kim avatar Byun Sang June avatar jeongjaehong avatar Jihoon Son avatar WangFengwei avatar Ashal aka JOKER avatar Arian Pasquali avatar Roberto Lapuente avatar Barak A. Pearlmutter avatar Torben Brodt avatar  avatar Wonmoon Song avatar Cho HyunJong avatar

Watchers

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ankus's Issues

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