PredictionIO: A Distributed Machine Learning Server for Practical Software Development

被引:17
|
作者
Chan, Simon [1 ]
Stone, Thomas [1 ]
Szeto, Kit Pang [2 ]
Chan, Ka Hou [2 ]
机构
[1] UCL, Dept Comp Sci, London, England
[2] TappingStone Inc, Walnut, CA USA
来源
PROCEEDINGS OF THE 22ND ACM INTERNATIONAL CONFERENCE ON INFORMATION & KNOWLEDGE MANAGEMENT (CIKM'13) | 2013年
关键词
Machine Learning Server; Algorithm Selection;
D O I
10.1145/2505515.2508198
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
One of the biggest challenges for software developers to build real-world predictive applications with machine learning is the steep learning curve of data processing frameworks, learning algorithms and scalable system infrastructure. We present PredictionIO, an open source machine learning server that comes with a step-by-step graphical user interface for developers to (i) evaluate, compare and deploy scalable learning algorithms, (ii) tune hyperparameters of algorithms manually or automatically and (iii) evaluate model training status. The system also comes with an Application Programming Interface (API) to communicate with software applications for data collection and prediction retrieval. The whole infrastructure of PredictionIO is horizontally scalable with a distributed computing component based on Hadoop. The demonstration shows a live example and workflows of building real-world predictive applications with the graphical user interface of PredictionIO, from data collection, algorithm tuning and selection, model training and re-training to real-time prediction querying.
引用
收藏
页数:3
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