Research on the Analysis of Skill Training Behavior and Accurate Evaluation Model Based on Artificial Intelligence
Year: 2024
Type: conference-paper
Abstract: This study analyzes skill training behaviors using three models: BP neural network, random forest, and support vector machine (SVM), assessing their classification accuracy across different tasks. Behavior data from an intelligent training platform was utilized, integrating feature extraction and model training to evaluate the performance of each model in behavior prediction. The results indicate that the SVM model achieved the highest accuracy on the test set, while the random forest model exhibited stable performance. This research provides valuable insights for precise evaluation of skill training, contributing to the optimization and promotion of intelligent training systems.
Authors: Songyun Jiang, Can Zhou, Yanan Huang
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
OpenAlex ID: W4409965434