Ensemble learning for data stream analysis: A survey

B Krawczyk, LL Minku, J Gama, J Stefanowski… - Information …, 2017 - Elsevier
In many applications of information systems learning algorithms have to act in dynamic
environments where data are collected in the form of transient data streams. Compared to …

Data fusion and multiple classifier systems for human activity detection and health monitoring: Review and open research directions

HF Nweke, YW Teh, G Mujtaba, MA Al-Garadi - Information Fusion, 2019 - Elsevier
Activity detection and classification using different sensor modalities have emerged as
revolutionary technology for real-time and autonomous monitoring in behaviour analysis …

Land use/land cover and change detection mapping in Rahuri watershed area (MS), India using the google earth engine and machine learning approach

CB Pande - Geocarto International, 2022 - Taylor & Francis
The change detection and land use and land cover (LULC) maps are more important
powerful forces behind numerous ecological systems and fallow land. The current research …

[PDF][PDF] Applied predictive modeling

M Kuhn - 2013 - blog.aml4td.org
This is a book on data analysis with a specific focus on the practice of predictive modeling.
The term predictive modeling may stir associations such as machine learning, pattern …

[图书][B] Ensemble methods: foundations and algorithms

ZH Zhou - 2012 - books.google.com
An up-to-date, self-contained introduction to a state-of-the-art machine learning approach,
Ensemble Methods: Foundations and Algorithms shows how these accurate methods are …

Automatic detection of Alzheimer's disease progression: An efficient information fusion approach with heterogeneous ensemble classifiers

S El-Sappagh, F Ali, T Abuhmed, J Singh, JM Alonso - Neurocomputing, 2022 - Elsevier
Predicting Alzheimer's disease (AD) progression is crucial for improving the management of
this chronic disease. Usually, data from AD patients are multimodal and time series in …

A survey of multiple classifier systems as hybrid systems

M Woźniak, M Grana, E Corchado - Information Fusion, 2014 - Elsevier
A current focus of intense research in pattern classification is the combination of several
classifier systems, which can be built following either the same or different models and/or …

Tweet sentiment analysis with classifier ensembles

NFF Da Silva, ER Hruschka, ER Hruschka Jr - Decision support systems, 2014 - Elsevier
Twitter is a microblogging site in which users can post updates (tweets) to friends (followers).
It has become an immense dataset of the so-called sentiments. In this paper, we introduce …

Statistical pattern recognition: A review

AK Jain, RPW Duin, J Mao - IEEE Transactions on pattern …, 2000 - ieeexplore.ieee.org
The primary goal of pattern recognition is supervised or unsupervised classification. Among
the various frameworks in which pattern recognition has been traditionally formulated, the …

[PDF][PDF] Cluster ensembles---a knowledge reuse framework for combining multiple partitions

A Strehl, J Ghosh - Journal of machine learning research, 2002 - jmlr.org
This paper introduces the problem of combining multiple partitionings of a set of objects into
a single consolidated clustering without accessing the features or algorithms that …