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Jubatus : Distributed Online Machine Learning Framework — Jubatus

Jubatus : Distributed Online Machine Learning Framework. Jubatus : Distributed Online Machine Learning Framework. Jubatus is a distributed processing framework and streaming machine learning library. Jubatus includes these functionalities:. Online Machine Learning Library: Classification, Regression, Recommendation (Nearest Neighbor Search), Graph Mining, Anomaly Detection, Clustering. Feature Vector Converter (fv converter): Data Preprocess and Feature Extraction. And Python / scikit-learn ( Jubakit.

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Jubatus : Distributed Online Machine Learning Framework — Jubatus | jubat.us Reviews

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Jubatus : Distributed Online Machine Learning Framework. Jubatus : Distributed Online Machine Learning Framework. Jubatus is a distributed processing framework and streaming machine learning library. Jubatus includes these functionalities:. Online Machine Learning Library: Classification, Regression, Recommendation (Nearest Neighbor Search), Graph Mining, Anomaly Detection, Clustering. Feature Vector Converter (fv converter): Data Preprocess and Feature Extraction. And Python / scikit-learn ( Jubakit.

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2 overview

3 quick start

4 tutorial

5 distributed mode

6 data conversion

7 algorithms

8 commands

9 client api

10 tips and faqs

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Jubatus : Distributed Online Machine Learning Framework — Jubatus | jubat.us Reviews

https://jubat.us

Jubatus : Distributed Online Machine Learning Framework. Jubatus : Distributed Online Machine Learning Framework. Jubatus is a distributed processing framework and streaming machine learning library. Jubatus includes these functionalities:. Online Machine Learning Library: Classification, Regression, Recommendation (Nearest Neighbor Search), Graph Mining, Anomaly Detection, Clustering. Feature Vector Converter (fv converter): Data Preprocess and Feature Extraction. And Python / scikit-learn ( Jubakit.

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No builds in the queue. Jubatus - Continuous Integration. Jubatus - Integration Tests. Test Result: 0 tests failing out of a total of 16 tests. Build stability: No recent builds failed. Develop) - Configure Matrix. 9 days 14 hr - #1190. 1 yr 1 mo - #973. 3 min 57 sec. Build stability: No recent builds failed. 9 days 15 hr - #1264. 1 mo 21 days - #1235. Build stability: 2 out of the last 5 builds failed. 21 days - #65. 22 days - #63. 2 hr 30 min. Test Result: 2 tests failing out of a total of 14 tests.

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1

Regression — Jubatus

http://jubat.us/en/tutorial/regression.html

Abstract of sample program. In this sample program, we will introduce how to use the linear regression function. Through the Jubatus Client. By using linear regression, we can estimate the output from the input data. This is useful for the power consumption forecast, stock price prediction, and etc. Abstract of sample program. In this sample, we will use a rent. Program to estimate the rent of a house, from the condition of the distance from the station, space, age, etc. Setting the HOST and RPC port of.

2

Jubatus : オンライン機械学習向け分散処理フレームワーク — Jubatus

http://jubat.us//ja

Jubatusは分散したデータを常に素早く深く分析することを狙った分散基盤技術です。オンライン機械学習ライブラリ: 多値分類、線形回帰、推薦近傍探索、グラフマイニング、異常検知、クラスタリング. 特徴ベクトル変換器 (fv converter): データの前処理と特徴抽出. Jubatus の最新バージョンは 0.9.3 ( ChangeLog. Jubatus は LGPL v2.1 の下で配布されています。 Red Hat Enterprise Linux 6.2 以降 (64-bit). その他の Linux 環境 (32-bit を含む). Classifier API: 学習(train) と分類(classify). CREATE STREAM FROM SELECT. CREATE STREAM FROM ANALYZE. CREATE STREAM FROM SLIDING WINDOW. Fork me on GitHub.

3

Cluster Administration Guide — Jubatus

http://jubat.us/en/admin.html

Building Jubatus from Source. This page describes how to administer a Jubatus cluster. For reliable Jubatus service, you should run Jubatus in a distributed environment. Additionally, to ensure high performance, you should carefully plan the process configuration of Jubatus servers and processes that Jubatus depends on. This is the process configuration that we recommend. Monitor the Jubatus Proxy processes. When the Jubatus Proxy goes down, block the access to the application from users. When running Ju...

4

Overview — Jubatus

http://jubat.us/en/overview.html

Difference from Hadoop and Mahout. In the coming era of extremely large databases, computer science will face new challenges in real Big Data applications such as nation-wide M2M sensor network analysis, online advertising optimization for millions of consumers, and real-time security monitoring on the raw Internet traffic. Jubatus is the first open source platform for online distributed machine learning on the data streams of Big Data. Our development team includes competent researchers who combine the ...

5

Architecture — Jubatus

http://jubat.us/en/processes.html

Jubatus has a client-server architecture. The simplest process configuration is single client process and single server process like following figure. Jubatus can make use of multiple server processes in order to scale out the system. By throwing queries to Jubatus Proxy, we can execute machine learning requests (update/analyze) with multiple server processes. Jubatus Proxy use ZooKeeper to keep-aliving and load-balancing each Jubatus servers.

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research.preferred.jp

オンライン機械学習（機械学習プロフェッショナルシリーズ第1期）発売のお知らせ | Preferred Research

https://research.preferred.jp/2015/04/olbook

著者はPreferred Infrastructure/Preferred Networksの海野, 岡野原, 得居, 徳永の4人です。機械学習の中でもオンライン機械学習に特化した本で、単純パーセプトロンから始まり、Passive Aggressive, Confidence Weighted, AROW, Soft Confidence Weightedなど Passive Aggressive, Confidence Weighted, AROWは分散オンライン機械学習フレームワークJubatus. Mail (will not be published) (required). Chainer MeetUP #03 を開催しました. SIGMOD Programming Contest 2016 優勝. Chainer MeetUP #03 を開催しました. SIGMOD Programming Contest 2016 優勝.

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得居誠也

http://www.beam2d.net/ja

得居誠也とくいせいやは株式会社Preferred Networks. のリサーチャーですまた，東京大学情報理工学系研究科の博士課程にも在籍しています得居は東京大学情報理工学系研究科数理情報学専攻で2012年に修士号を取得し，現在は深層学習フレームワーク Chainer のリード開発者をしています現在の主な研究開発対象は深層学習，そのソフトウェア設計，コンピュータビジョン，および自然言語処理です. 東京大学情報理工学系研究科コンピュータ科学専攻 (2016/4 現在). 東京大学情報理工学系研究科数理情報学専攻 (2010/04 2012/03). 修士論文 Learning Hash with Sequential Buckets Partitioning 逐次的なバケット分割によるハッシュの学習. 東京大学理学部数学科 (2006/04 2010/03). 栄光学園中学高等学校 (2000/04 2006/03) 54期生. エンジニアリサーチャー (2012/04 2014/10). 海野裕也, 岡野原大輔, 得居誠也. 佐藤一誠, 中川裕志. 最近傍探索のため...

repeatedly.github.io

Works - Go ahead!

http://repeatedly.github.io/works

Fast and Compact Serialization. Now working) : ArangoDB Driver. Author of MessagePack for D. And MessagePack RPC for Python. D言語の設計と進化とか : The Design and Evolution of D. はじめてのFluentdプラグインの書き方指南 : How to write a plugin of Fluentd. 概説Tornado : Introduction to Tornado. Engineer at Treasure Data, Inc. Tokyo Apache Drill Meetup 第一回. YAPC: Asia Tokyo 2015での発表. YAPC: Asia 2015 talk. Fluentd meetup 2015 summer.

tanakh.jp

エラー処理を書いてはいけない

http://tanakh.jp/pub/pfi-seminar-2011-12-08.html

田中英行 tanaka.hideyuki@gmail.com. 田中英行 (@tanakh, http:/ tanakh.jp. パーザジェネレータ & QQ w/ AQ). シューティングゲーム) / ( Monadius. Learn you a Haskell. Malloc / free, new / delete. Fopen / fclose, etc. Http:/ www.slideshare.net/pfi/ss-9780450. Concurrent Revisions, etc. Fopen, java.util.Map.get() など. 一般的なオブジェクト指向言語は、基本的に全てのオブジェクトへの参照が nullable であるため、エラー通知を行うために返り値を変える必要がない. 返り値として null が返る可能性があるか、ドキュメントを確認しないといけない. いろいろな実装がありますが、大半は throw で例外オブジェクトを投げて、 catchで拾う形. Scope & destructor (C ). Using (C#), Java7 の try.

micassoc.blogspot.com

Jubatusとは ~ SAN・ストレージ用語解説

http://micassoc.blogspot.com/2011/11/jubatus.html

8Gb RAID ストレージ XRS F6512E. 読み方は「ユバタス」。学名「Acinonyx jubatus」とは「チーター」のこと。 2011年10月、日本電信電話株式会社（NTT）と株式会社プリファードインフラストラクチャーが開発し、同年は26日より公開した。 OSS. 読み方は「レイドゴジュウ」または「レイドゴーゼロ」。「RAID 5 0」とも表記される。 RAID 5と RAID 0 を組み合わせた構成のこと。 RAID 5の書込みにはパリティのデータ照合が必要なことから、オーバーヘッドがあるが、 RAID 0 と組合わせることによ. 英語表記は、「Random Access」。記録媒体に書込み、または、読出しをする際の方法の１つ。非連続に編成されたファイルデータの配置情報をインデックスから割り出し、直接必要なデータにアクセスする方法をいう。またそのような非連続に編成された方式のファイルをランダムアクセス. Fibre Channel over Ethernet. Poor man’s SAN. Design by Free WordPress Themes.

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Jubatus : Distributed Online Machine Learning Framework — Jubatus

Jubatus : Distributed Online Machine Learning Framework. Jubatus : Distributed Online Machine Learning Framework. Jubatus is a distributed processing framework and streaming machine learning library. Jubatus includes these functionalities:. Online Machine Learning Library: Classification, Regression, Recommendation (Nearest Neighbor Search), Graph Mining, Anomaly Detection, Clustering. Feature Vector Converter (fv converter): Data Preprocess and Feature Extraction. And Python / scikit-learn ( Jubakit.

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