A Novel Ensemble Classifier Framework to Preprocess, Learn and Predict Imbalanced Heterogeneous Drifted Data Stream-Reference-Cited by-同舟云学术

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A Novel Ensemble Classifier Framework to Preprocess, Learn and Predict Imbalanced Heterogeneous Drifted Data Stream

Published:2023-04-05 Issue: Volume: Page:
ISSN:
Container-title:2023 Second International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)
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Author:

D Paulraj¹,Prem M Vigilson²

Affiliation:

1. R. M. K. Engineering College,Department of Computer Science and Engineering,Chennai,India

2. R. M. K. College of Engineering and Technology,Department of Computer Science and Engineering,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10156871/10156874/10157417.pdf?arnumber=10157417

Reference25 articles.

1. A gradient boosted decision tree-based sentiment classification of twitter data

2. An automated exploring and learning model for data prediction using balanced CA-SVM

3. ANN and fuzzy based household energy consumption prediction with high accuracy

4. Effective Data Storage and Dynamic Data Auditing Scheme for Providing Distributed Services in Federated Cloud

5. Multilayer Stacked Probabilistic Belief Network-Based Brain Tumor Segmentation and Classification

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1. Fair-CMNB: Advancing Fairness-Aware Stream Learning with Naïve Bayes and Multi-Objective Optimization;Big Data and Cognitive Computing;2024-01-31

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