基于C#最近邻算法的教学系统分析与设计

Analysis and Design of KNN Teaching System Based on C#

  • 摘要: K-近邻分类(KNN)是著名的模式识别统计学方法之一,被广泛应用于文本分类、图像处理等领域。因其实现思想的简单性及基于实例的分类方法,可作为人工智能课程的入门案例算法。由于KNN分类识别过程中懒散的学习方式,在理论与实践教学上存在着一定的难度。通过对KNN算法的研究和软件教学系统的分析与设计,实现了基于Visual C#的KNN各种演示方法和辅助教学系统;改进了教学手段,提高了教学质量。

     

    Abstract: KNN (K-nearest neighbor) is the most famous pattern recognition statistical method,and it is widely used in text classification,image processing and other fields.Because of simplicity and realization based on case classification method,KNN can be used as entry case algorithm of artificial intelligence courses .For the lazy learning method in KNN classification process,it has some difficulty in the theory and practice teaching.According the study of KNN algorithm and the analysis and design of software teaching system,it has achieved the teaching system based on Visual C#,and includes practical teaching,improving the teaching methods and the quality of teaching.

     

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