A TLBO Based Bagging Approach for Effective Disease Diagnosis-Reference-Cited by-同舟云学术

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A TLBO Based Bagging Approach for Effective Disease Diagnosis

Published:2024-01-04 Issue: Volume:16 Page:284-289
ISSN:
Container-title:Proceedings of the 7th Joint International Conference on Data Science & Management of Data (11th ACM IKDD CODS and 29th COMAD)
language:
Short-container-title:

Author:

Arukonda Srinivas¹^ORCID,Cheruku Ramalingaswamy¹^ORCID

Affiliation:

1. Computer Science and Engineering, National Institute of Technology Warangal, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3632410.3632411

Reference26 articles.

1. Comparing supervised and semi-supervised Machine Learning Models on Diagnosing Breast Cancer

2. Comparing Oversampling Techniques to Handle the Class Imbalance Problem: A Customer Churn Prediction Case Study

3. Srinivas Arukonda and Ramalingaswamy Cheruku. 2023. A novel diversity-based ensemble approach with genetic algorithm for effective disease diagnosis. Soft Computing (2023), 1–20.

4. Investigation of Lung Cancer detection Using 3D Convolutional Deep Neural Network

5. A bi-objective optimization method to produce a near-optimal number of classifiers and increase diversity in Bagging

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