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Cloud Guided Stream Classification Using Class-Based Ensemble
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-642-01307-2_34openalex-snapshot
A Multi-partition Multi-chunk Ensemble Technique to Classify Concept-Drifting Data Streams
inferredcites →https://doi.org/10.1007/978-3-642-04174-7_6openalex-snapshot
Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams
inferredcites →https://doi.org/10.1007/978-3-642-10665-1_71openalex-snapshot
Parallel K-Means Clustering Based on MapReduce
inferredcites →https://doi.org/10.1080/095400996116839openalex-snapshot
Error Correlation and Error Reduction in Ensemble Classifiers
inferredcites →https://doi.org/10.1109/chinagrid.2009.39openalex-snapshot
MReC4.5: C4.5 Ensemble Classification with MapReduce
inferredcites →https://doi.org/10.1109/icdm.2007.96openalex-snapshot
On Appropriate Assumptions to Mine Data Streams: Analysis and Practice
inferredcites →https://doi.org/10.1109/icdm.2009.76openalex-snapshot
Mining Data Streams with Labeled and Unlabeled Training Examples
inferredcites →https://doi.org/10.1109/tkde.2006.69openalex-snapshot
A framework for on-demand classification of evolving data streams
inferredcites →https://doi.org/10.1145/1081870.1081961openalex-snapshot
Combining proactive and reactive predictions for data streams
inferredcites →https://doi.org/10.1145/1102351.1102408openalex-snapshot
Using additive expert ensembles to cope with concept drift
inferredcites →https://doi.org/10.1145/1557019.1557041openalex-snapshot
New ensemble methods for evolving data streams
inferredcites →https://doi.org/10.1145/502512.502529openalex-snapshot
Mining time-changing data streams
inferredcites →https://doi.org/10.1145/956750.956778openalex-snapshot
Mining concept-drifting data streams using ensemble classifiers
inferredcites →https://doi.org/10.1145/956755.956778openalex-snapshot
Mining concept-drifting data streams using ensemble classifiers
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-319-93034-3_2openalex-snapshot
Social Stream Classification with Emerging New Labels
inferred← citeshttps://doi.org/10.1007/s10115-023-02018-xopenalex-snapshot
Review on novelty detection in the non-stationary environment
inferred← citeshttps://doi.org/10.1007/s10462-015-9444-8openalex-snapshot
Novelty detection in data streams
inferred← citeshttps://doi.org/10.1007/s10618-015-0433-yopenalex-snapshot
MINAS: multiclass learning algorithm for novelty detection in data streams
inferred← citeshttps://doi.org/10.1007/s10618-025-01124-4openalex-snapshot
ARM-stream: active recovery of miscategorizations in clustering-based data stream classifiers
inferred← citeshttps://doi.org/10.1007/s10994-015-5515-yopenalex-snapshot
Learning from evolving video streams in a multi-camera scenario
inferred← citeshttps://doi.org/10.1007/s10994-023-06353-6openalex-snapshot
A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework
inferred← citeshttps://doi.org/10.1016/j.eswa.2016.11.028openalex-snapshot
Applying a kernel function on time-dependent data to provide supervised-learning guarantees
inferred← citeshttps://doi.org/10.1109/bigdata.congress.2013.58openalex-snapshot
Labeling Instances in Evolving Data Streams with MapReduce
inferred← citeshttps://doi.org/10.1109/cloud.2014.82openalex-snapshot
Evolving Big Data Stream Classification with MapReduce
inferred← citeshttps://doi.org/10.1109/cloudcom.2013.152openalex-snapshot
Intelligent MapReduce Based Framework for Labeling Instances in Evolving Data Stream
inferred← citeshttps://doi.org/10.1109/icdmw.2013.145openalex-snapshot
MapReduce Based Frameworks for Classifying Evolving Data Stream
inferred← citeshttps://doi.org/10.1109/icpr.2014.224openalex-snapshot
Active Learning from Video Streams in a Multi-camera Scenario
inferred← citeshttps://doi.org/10.1109/ictai.2017.00077openalex-snapshot
Concept Drift Detection for Graph-Structured Classifiers under Scarcity of True Labels
inferred← citeshttps://doi.org/10.1109/tkde.2015.2441713openalex-snapshot
Evaluation of Multiclass Novelty Detection Algorithms for Data Streams
inferred← citeshttps://doi.org/10.1145/3349265openalex-snapshot
A Comprehensive Survey on Cloud Data Mining (CDM) Frameworks and Algorithms
inferred← citeshttps://doi.org/10.11606/t.55.2014.tde-14072014-142248openalex-snapshot
Detecção de novidade em fluxos contínuos de dados multiclasse
inferred← citeshttps://doi.org/10.1201/ebk1439826119-15openalex-snapshot
Novelty Detection in Data Streams
inferred← citeshttps://doi.org/10.1201/ebk1439826119-c9openalex-snapshot
Novelty Detection in Data Streams
inferred← citeshttps://doi.org/10.3233/jhs-160535openalex-snapshot
A parallelized network traffic classification framework based on selective ensemble and diversity measures
inferred← citeshttps://doi.org/10.4108/icst.collaboratecom.2013.254135openalex-snapshot
MapReduce-Guided Scalable Compressed Dictionary Construction for Evolving Repetitive Sequence Streams
inferred← citeshttps://doi.org/10.5821/dissertation-2117-121198openalex-snapshot
Data driven methods for updating fault detection and diagnosis system in chemical processes
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