Adaptive Online Sequential ELM for Concept Drift Tackling

Adaptive Online Sequential ELM for Concept Drift Tackling

A machine learning method needs to adapt to over time changes in the environment. Such changes are known as concept drift. In this paper, we propose concept drift tackling method as an enhancement of Online Sequential Extreme Learning Machine (OS-ELM) and Constructive Enhancement OS-ELM (CEOS-ELM) b...

Full description

Bibliographic Details
Main Authors:	Arif Budiman, Mohamad Ivan Fanany, Chan Basaruddin
Format:	Article
Language:	English
Published:	Hindawi Limited 2016-01-01
Series:	Computational Intelligence and Neuroscience
Online Access:	http://dx.doi.org/10.1155/2016/8091267

Similar Items

FnnmOS-ELM: A Flexible Neural Network Mixed Online Sequential Elm
by: Xiali Li, et al.
Published: (2019-09-01)

GSOS-ELM: An RFID-Based Indoor Localization System Using GSO Method and Semi-Supervised Online Sequential ELM
by: Fagui Liu, et al.
Published: (2018-06-01)

A New Data Representation Based on Training Data Characteristics to Extract Drug Name Entity in Medical Text
by: Mujiono Sadikin, et al.
Published: (2016-01-01)

Online Sequential Complex-Valued ELM for Noncircular Signals: Augmented Structures and Learning Algorithms
by: Hui Wang, et al.
Published: (2021-01-01)

Online Ensemble Using Adaptive Windowing for Data Streams with Concept Drift
by: Yange Sun, et al.
Published: (2016-05-01)

Handling latency for online learning with concept drift
by: Marrs, Gary Russell
Published: (2011)

The concept of a tree or «Ode to Elm»
by: H S Mukhamadiev, et al.
Published: (2014-12-01)

Domain Adaption Based on ELM Autoencoder
by: Wan-Yu Deng, et al.
Published: (2017-01-01)

Dynamic Unlearning for Online learning on Concept-drifting Data
by: Sheng-Chi You, et al.
Published: (2015)

Comparative wood anatomy of Wych Elm, English Elm, Caucasian Elm and Hackberry
by: Vahid reza Safdari, et al.
Published: (2011-09-01)

Structural drift: the population dynamics of sequential learning.
by: James P Crutchfield, et al.
Published: (2012-01-01)

An Adaptive Behavioral-Based Incremental Batch Learning Malware Variants Detection Model Using Concept Drift Detection and Sequential Deep Learning
by: Abdulbasit A. Darem, et al.
Published: (2021-01-01)

Faults and Concept Drifts Detection and Adaptation of Wind Turbines
by: Wu, Tsun-Yuan, et al.
Published: (2019)

An adaptive framework for classification of concept drift with limited supervision
by: Conca, Piero
Published: (2012)

ELM
Published: ()

Exploring the Effect of the Cues of Online-advertising on Online-shopping Behavior Based on ELM
by: Hung-Ru Chang, et al.
Published: (2010)

Online Active Learning Paired Ensemble for Concept Drift and Class Imbalance
by: Hang Zhang, et al.
Published: (2018-01-01)

Hybrid Structure-Adaptive RBF-ELM Network Classifier
by: Hui Wen, et al.
Published: (2017-01-01)

Sequential testing of the sign of the drift of a Brownian motion
by: Karimidamavandi, Ashkan
Published: (2021)

Recurrent Adaptive Classifier Ensemble for Handling Recurring Concept Drifts
by: Tinofirei Museba, et al.
Published: (2021-01-01)

Concept drift learning and its application to adaptive information filtering
by: Widyantoro, Dwi Hendratmo
Published: (2004)

Adapting the dynamic selection of classifiers approach for concept drift scenarios
by: Almeida, Paulo Ricardo Lisboa de
Published: (2018)

An ELM Based Online Soft Sensing Approach for Alumina Concentration Detection
by: Sen Zhang, et al.
Published: (2015-01-01)

Overview of Bayesian sequential testing for the drift of a Wiener process
by: Vogli, Aleksander
Published: (2021)

An adaptive learning system for time series forecasting in the presence of concept drift
by: CAVALCANTE, Rodolfo Carneiro
Published: (2018)

Adaptive Incremental-Learning Ensemble Classification Approach for Concept Drift Problem
by: HAN Mingming, SUN Guanglu, ZHU Suxia
Published: (2020-07-01)

Dutch elm disease and elm bark beetles: a century of association
by: Santini A, et al.
Published: (2015-04-01)

Endophytic fungi in Elms : implications for the integrated management of Dutch Elm Disease
by: Blumenstein, Kathrin
Published: (2015)

An Online Calibration Method for a Galvanometric System Based on Wavelet Kernel ELM
by: Wugang Zhang, et al.
Published: (2019-03-01)

Dendroclimatology of Elm in London
by: Brett, Donald W.
Published: (1978)

The Dutch elm disease
by: Townsend, Katherine Rowena
Published: (2013)

Concept Drift in Surgery Prediction
by: Beyene, Ayne, et al.
Published: (2012)

An Overview on Concept Drift Learning
by: Adriana Sayuri Iwashita, et al.
Published: (2019-01-01)

Electromagnetic ELM and inter-ELM filaments detected in the COMPASS Scrape-Off Layer
by: M. Spolaore, et al.
Published: (2017-08-01)

Bayesian sequential testing of the drift of a multi-dimensional Brownian motion
by: Valachi, Georgia
Published: (2020)

Adaptive Abnormal Oil Temperature Diagnosis Method of Transformer Based on Concept Drift
by: Zhibin Zhao, et al.
Published: (2021-07-01)

Concept Drift Adaptation Techniques in Distributed Environment for Real-World Data Streams
by: Hassan Mehmood, et al.
Published: (2021-03-01)

Adaptive Online Sequential Extreme Learning Machine with Kernels for Online Ship Power Prediction
by: Xiuyan Peng, et al.
Published: (2021-08-01)

Load Forecasting Under Concept Drift: Online Ensemble Learning With Recurrent Neural Network and ARIMA
by: Rashpinder Kaur Jagait, et al.
Published: (2021-01-01)

Detection of phytoplasmal DNA in flowers and seeds from elm trees infected with Elm Yellows
by: A. Sfalanga, et al.
Published: (2002-12-01)