Predicting Abundance of Fish Species Populations in Manila Bay, Philippines Based on Ensemble Learning Approach-Reference-Cited by-同舟云学术

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Predicting Abundance of Fish Species Populations in Manila Bay, Philippines Based on Ensemble Learning Approach

Published:2023-06-28 Issue: Volume: Page:
ISSN:
Container-title:2023 20th International Joint Conference on Computer Science and Software Engineering (JCSSE)
language:
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Author:

Rasdas Sherrlyn M.¹,Fajardo Arnel C.²,Limbago Jomel S.³

Affiliation:

1. Graduate Program Technological Institute of the Philippines Manila,Philippines

2. College of Computing Science, Information and Communication Technology -CCSICT Isabela State University-Cauayan,Philippines

3. Cavite State University Naic,Fisheries and Aquatic Sciences Department (FASD),Cavite,Philippines

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10201904/10201936/10201953.pdf?arnumber=10201953

Reference22 articles.

1. A machine learning-based approach for smart agriculture via stacking-based ensemble learning and feature selection methods

2. A personal credit forecasting method based on Stacking ensemble learning

3. Improved ensemble learning for classification techniques based on majority voting

4. Scalable ensemble learning and computationally efficient variance estimation;ledell;Graduate Division University of California Berkeley,2015

5. A Machine Learning Strategy for the Quantitative Analysis of the Global Warming Impact on Marine Ecosystems

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