Accurate Prediction of Object Classification Based on Patterns Using Linear Regression in Comparison with Enhanced K-Nearest Neighbor

G. Kumar, K. Anbazhagan

2023

Abstract

The Project aim is to recognise the pattern that was seen in the photograph and to recognise and categorize the object that it represents. Whether the image pattern will be applied to face recognition, image classification, or fingerprint identification. Materials and Methods: The prediction of image recognition from the input picture is carried out using the Novel Linear Regression classifier and k Nearest Neighbor classifier. The Kaggle database system served as the source for the research dataset used in this study. A sample size of twenty (Group 1=10 and from Group 2=10) was used to predict visual pattern analysis with an enhanced precision rate. The computation made use of a G-power of 0.8, alpha and beta values of 0.05 and 0.2, and a confidence range of 95%. Results: The recommended Novel Linear Regression has an accuracy rate of 88.09%, which is much greater than the k nearest neighbor algorithm's accuracy rate of 85.33%. Considering the research, it can be said that the two algorithms differ statistically significantly for p = 0.001 (Independent Sample T Test P0.05).In conclusion, the proposed Novel Linear Regression model outperforms the k nearest neighbor method in terms of performance evaluation of visual pattern analysis recognition accuracy.

Paper Citation

in Harvard Style

Kumar G. and Anbazhagan K. (2023). Accurate Prediction of Object Classification Based on Patterns Using Linear Regression in Comparison with Enhanced K-Nearest Neighbor. In Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT; ISBN 978-989-758-661-3, SciTePress, pages 373-377. DOI: 10.5220/0012772500003739

in Bibtex Style

@conference{ai4iot23,
author={G. Kumar and K. Anbazhagan},
title={Accurate Prediction of Object Classification Based on Patterns Using Linear Regression in Comparison with Enhanced K-Nearest Neighbor},
booktitle={Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT},
year={2023},
pages={373-377},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012772500003739},
isbn={978-989-758-661-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Artificial Intelligence for Internet of Things: Accelerating Innovation in Industry and Consumer Electronics - Volume 1: AI4IoT
TI - Accurate Prediction of Object Classification Based on Patterns Using Linear Regression in Comparison with Enhanced K-Nearest Neighbor
SN - 978-989-758-661-3
AU - Kumar G.
AU - Anbazhagan K.
PY - 2023
SP - 373
EP - 377
DO - 10.5220/0012772500003739
PB - SciTePress