[PDF][PDF] Incremental rule-based learners for handling concept drift: an overview

M Deckert - Foundations of Computing and Decision Sciences, 2013 - sciendo.com
Learning from non-stationary environments is a very popular research topic. There already
exist algorithms that deal with the concept drift problem. Among them there are online or …

Online mass flow prediction in CFB boilers with explicit detection of sudden concept drift

M Pechenizkiy, J Bakker, I Žliobaitė… - ACM SIGKDD …, 2010 - dl.acm.org
Fuel feeding and inhomogeneity of fuel typically cause fluctuations in the circulating
fluidized bed (CFB) process. If control systems fail to compensate the fluctuations, the whole …

Adaptive training set formation

I Žliobaitė - 2010 - epublications.vu.lt
Abstract [eng] Nowadays, when the environment is changing rapidly and dynamically, there
is a particular need for adaptive data mining methods.Spam'filters, personalized …

Quantile index for gradual and abrupt change detection from cfb boiler sensor data in online settings

A Maslov, M Pechenizkiy, T Kärkkäinen… - Proceedings of the Sixth …, 2012 - dl.acm.org
In this paper we consider the problem of online detection of gradual and abrupt changes in
sensor data having high levels of noise and outliers. We propose a simple heuristic method …

Handling abrupt changes in evolving time-series data

J Bakker - 2012 - research.tue.nl
Forecasting and online classification are challenging tasks for the current day industry.
Under the influence of many unobservable factors, the concepts that are derived from data …

[PDF][PDF] Educational Qualifications

M Ch - 1992 - valvesofheart.org
BIO - DATA Page 1 BIO - DATA Name : A. Sampath Kumar ADDRESS Office Pushpanjali
crosslay Hospital W 3 Sector 1,Vaishali,Ghaziabad 201012 Residence A 4(first floor) Yojana …

[引用][C] Concept Change in Machine Learning

M Hawes…

[引用][C] Vehicles, Data and Cities

W Epple