Construction of Music Teaching Evaluation Model Based on Weighted Naïve Bayes

Evaluation of music teaching is a highly subjective task often depending upon experts to assess both the technical and artistic characteristics performance from audio signal. This article explores building computational models for evaluating using machine learning algorithms. As one widely used methods build classifiers, Naïve Bayes algorithm has become most popular evaluation because its strong prior knowledge, features, high classification performance. In this article, we propose model based on weighted algorithm. Moreover, Bayesian incremental approach employed improve efficiency system. Experimental results show that proposed in paper superior other algorithms context evaluation.