Optimization Strategy of Small-Sample Subjective Education Evaluation System Driven by Artificial Intelligence:An Integrated Application Study of Solation Forest and Kendall's Harmony Coefficient
This study explores the application of artificial intelligence technology in the small-sample subjective education evaluation system,and uses the solation forest algorithm and Kendall's harmony coefficient algorithm to build an AI-based supervision and inspection system to optimize both evaluators and scores.The research results show that this system has excellent performance in practical teaching scenarios,and can significantly improve the accuracy and reliability of evaluation results,which can not only provide optimization strategies for education evaluation systems,but also provide theoretical support and practical guidance for data-driven decision-making in related fields.
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