White Papers

Incremental Info-Fuzzy Algorithm for Real Time Data Mining of Non-Stationary Data Streams

Overview Most real-world data streams are generated by non-stationary processes that may change drastically over time. In the previous work, the author has presented a real-time data mining algorithm called OLIN (On-Line Information Network), which adapts itself automatically to the rate of concept drift in a non-stationary data stream by repeatedly constructing a new model from a sliding window of latest examples. This paper introduces an incremental version of the OLIN algorithm, which saves a significant amount of computational effort by updating an existing model as long as no concept drift is detected. The approach is evaluated on large real-world streams of traffic and stock data.

Download White Paper

By downloading you agree to our Terms and Conditions. These include information regarding use of your personal data.

Publisher
Ben-Gurion University of the Negev
File Format
PDF
Date Published
Oct 1, 2008
Format
White Papers
Topics
Knowledge and Data Management, Data Mining - Analysis, Software Engineering

Similiar White Papers

Improving Credit Scoring by Generalized Additive Model

Improving Credit Scoring by Generalized Additive Model

Logistic Regression has been widely used in the financial service industry for credit scoring models. Despite its advant

Publisher: SAS Institute  |  Tags: computing

Optimize your performance with the Smart Work Advisor

Optimize your performance with the Smart Work Advisor

Smart Work Advisor shows how businesses can optimize their performance by providing a decision tree they can use to adap

Publisher: IBM