Classification of word difficulty using M-SVM algorithm

Yu Zhang; Ziyang Li; Junjie Lu; Mengyue Chong; Chen Du; Tiantian Zhao; Benmao Cheng

doi:10.1117/12.3005844

10 October 2023 Classification of word difficulty using M-SVM algorithm

Yu Zhang, Ziyang Li, Junjie Lu, Mengyue Chong, Chen Du, Tiantian Zhao, Benmao Cheng

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 127991K (2023) https://doi.org/10.1117/12.3005844
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Objective: The aim of this study is to develop a classification model based on word attributes and address the classification problem of word difficulty. Methods: We constructed word indexes for difficulty classification based on structure and usage habits, and then trained the SVM classification model using the constructed database. The optimal penalty coefficient C was determined using Monte Carlo simulation with the dichotomous method to optimize the iterative process. Finally, we evaluated the model objectively using five-fold cross-validation and model comparison. Results: The experimental results showed that the highest classification accuracy of 98.4% and 82% for the training and prediction sets, respectively, was achieved when the optimal penalty coefficients were calculated to be (944, 273, 756, 1064, 671). The average classification accuracy obtained by five-fold cross-validation was 0.892. Comparison with other classification models indicated that this model improved the classification accuracy. In summary, the M-SVM model showed better robustness in solving the multi-classification problem, to some extent avoiding the overfitting phenomenon and demonstrating a better classification effect.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yu Zhang, Ziyang Li, Junjie Lu, Mengyue Chong, Chen Du, Tiantian Zhao, and Benmao Cheng "Classification of word difficulty using M-SVM algorithm", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 127991K (10 October 2023); https://doi.org/10.1117/12.3005844

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KEYWORDS

Data modeling

Monte Carlo methods

Education and training

Computer simulations

Cross validation

Statistical modeling

Image classification

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