Improving Prediction Accuracy in Drift Detection Using Random Forest in Comparing with Modified Light Gradient Boost Model-Reference-Cited by-同舟云学术

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Improving Prediction Accuracy in Drift Detection Using Random Forest in Comparing with Modified Light Gradient Boost Model

Published:2024-04-04 Issue: Volume: Page:1-4
ISSN:
Container-title:2024 Ninth International Conference on Science Technology Engineering and Mathematics (ICONSTEM)
language:
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Author:

Likitha N Raja¹,Nagalakshmi J T²

Affiliation:

1. Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences,Dept of ECE,Chennai,India

2. Saveetha Institute of Medical and Technical Sciences,Department of VLSI Micro Electronics, Saveetha School of Engineering,Chennai,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10568576/10568577/10568896.pdf?arnumber=10568896

Reference11 articles.

1. Dataset Shift in Machine Learning

2. Effective control of non linear parameters using artificial intelligence;T. M.,2016

3. Concept Drift Detection in Histogram-Based Straightforward Data Stream Prediction

4. Intelligent Door Knocking Security System Using IOT

5. Predicting Melancholy risk among IT professionals using Modified Deep Learning Neural Network (MDLNN);R,2022

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