Results 61 to 70 of about 5,397,718 (323)

Online Machine Learning from Non-stationary Data Streams in the Presence of Concept Drift and Class Imbalance: A Systematic Review

Journal of ICT
In IoT environment applications generate continuous non-stationary data streams with in-built problems of concept drift and class imbalance which cause classifier performance degradation.
Abdul Sattar Palli, Jafreezal Jaafar, Abdul Rehman Gilal, Aeshah Alsughayyir, Heitor Murilo Gomes, Abdullah Alshanqiti, Mazni Omar   +6 more
doaj   +1 more source

Nonparametric model reconstruction for stochastic differential equation from discretely observed time-series data [PDF]

, 2011
A scheme is developed for estimating state-dependent drift and diffusion coefficients in a stochastic differential equation from time-series data. The scheme does not require to specify parametric forms for the drift and diffusion coefficients in advance.
Ohkubo, Jun
core   +2 more sources

Benchmarking Change Detector Algorithms from Different Concept Drift Perspectives

Future Internet, 2023
The stream mining paradigm has become increasingly popular due to the vast number of algorithms and methodologies it provides to address the current challenges of Internet of Things (IoT) and modern machine learning systems.
G. Y. Sakurai, J. F. Lopes, B. Zarpelão, Sylvio Barbon Junior   +3 more
semanticscholar   +1 more source

Understanding Concept Drift

, 2017
Concept drift is a major issue that greatly affects the accuracy and reliability of many real-world applications of machine learning. We argue that to tackle concept drift it is important to develop the capacity to describe and analyze it. We propose tools for this purpose, arguing for the importance of quantitative descriptions of drift in marginal ...
Webb, Geoffrey I., Lee, Loong Kuan, Petitjean, François, Goethals, Bart   +3 more
openaire   +2 more sources

Regional Concept Drift Detection and Density Synchronized Drift Adaptation [PDF]

Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017
In data stream mining, the emergence of new patterns or a pattern ceasing to exist is called concept drift. Concept drift makes the learning process complicated because of the inconsistency between existing data and upcoming data. Since concept drift was first proposed, numerous articles have been published to address this issue in terms of ...
Anjin Liu, Yiliao Song, Guangquan Zhang, Jie Lu   +3 more
openaire   +1 more source

Patient Activation in Childhood, Adolescent, and Young Adult Cancer Survivors: Current Insights and Implications for Survivorship Care—A Systematic Review From the e‐QuoL Project

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Purpose Patient activation—encompassing knowledge, confidence, and skills in managing individual's health—is a cornerstone of person‐centered care. However, its significance among childhood, adolescent, and young adult cancer survivors (CAYACS) remains unexplored. This article examines the application of the 13‐item Patient Activation Measure (
Charlotte Demoor‐Goldschmidt, Anne Maas, Gisela Michel, Amandine Bertrand, Kristen E. T. Thornton, Martine Bellanger, Anna‐Liesa Filbert, Desiree Grabow, Monica Muraca, Katharina Roser, Sara Oberti, Jelena Roganovic, Hanne Cathrine Lie   +12 more
wiley   +1 more source

Aging Studies for the Large Honeycomb Drift Tube System of the Outer Tracker of HERA-B

, 2003
The HERA-B Outer Tracker consists of drift tubes folded from polycarbonate foil and is operated with Ar/CF4/CO2 as drift gas. The detector has to stand radiation levels which are similar to LHC conditions.
Albrecht, H, Bauer, T S, Beck, M, Belkov, A, Berkhan, K, Bohm, G, Bruinsma, M, Buran, T, Capeans, M, Chamanina, J, Chen, BX, Deckers, H, Dehmelt, K, Dong, X, Eckmann, R, Emelianov, D, Fourletov, S, Golutvin, I, Hoepfner, Kerstin, Hohlmann, M, Hulsbergen, W, Jia, Y, Jiang, C, Kapitza, H, Karabekyan, S, Ke, Z, Kiryushin, Y, Kolanoski, H, Korpar, S, Krizan, P, Krucker, D, Lanyov, A, Liu, Y Q, Lohse, T, Loke, R, Mankel, R, Medin, G, Michel, E, Moshkin, A, Ni, J, Nowak, S, Ouchrif, M, Padilla, C, Pose, D, Ressing, D, Saveliev, V, Schmidt, B, Schmidt-Parzefall, W, Schreiner, A, Schwanke, U, Schwarz, Andreas S, Siccama, I, Solunin, S, Somov, S, Souvorov, V, Spiridonov, A, Staric, M, Stegmann, C, Steinkamp, O, Tesch, N, Tsakov, I, Uwer, U, Vassiliev, S, Vukotic, I, Walter, M, Wang, J J, Wang, Y M, Wurth, R, Yang, J, Zheng, Z, Zhu, Z, Zimmerman, R   +71 more
core   +1 more source

European Standard Clinical Practice Guideline and EXPeRT Recommendations for the Diagnosis and Management of Gastroenteropancreatic Neuroendocrine Neoplasms in Children and Adolescents

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Pediatric gastroenteropancreatic neuroendocrine neoplasms (GEP‐NENs) are extremely rare and clinically heterogeneous. Management has largely been extrapolated from adult practice. This European Standard Clinical Practice Guideline (ESCP), developed by the EXPeRT network in collaboration with adult NEN experts, provides (adult) evidence ...
Michaela Kuhlen, Calogero Virgone, Antje Redlich, Michael Abele, Ricardo Lopez‐Almaraz, Tal Ben‐Ami, Ewa Bien, Gianni Bisogno, Maja Mazic Cesen, Andrea Ferrari, Malgorzata A. Krawczyk, Yves Reguerre, Dominik T. Schneider, Ines B. Brecht, Charlotte Rigaud, Bilgehan Yalcin, Rainer Claus, Christian Vokuhl, Constantin Lapa, Jörg Fuchs, Segolene Hescot, Thomas Walter, Julien Hadoux, Daniel Orbach   +23 more
wiley   +1 more source

An Incremental Construction of Deep Neuro Fuzzy System for Continual Learning of Non-stationary Data Streams

, 2019
Existing FNNs are mostly developed under a shallow network configuration having lower generalization power than those of deep structures. This paper proposes a novel self-organizing deep FNN, namely DEVFNN. Fuzzy rules can be automatically extracted from
Pedrycz, Witold, Pratama, Mahardhika, Webb, Geoffrey I.   +2 more
core   +1 more source

On the Hardness and Necessity of Supervised Concept Drift Detection

International Conference on Pattern Recognition Applications and Methods, 2023
: The notion of concept drift refers to the phenomenon that the distribution generating the observed data changes over time. If drift is present, machine learning models can become inaccurate and need adjustment. Many technologies for learning with drift
Fabian Hinder, Valerie Vaquet, Johannes Brinkrolf, Barbara Hammer   +3 more
semanticscholar   +1 more source