Improved KNN Classification Algorithm by Dynamic Obtaining K

KNN algorithm which is one of the best methods of text classifying in the vector space model (VSM) is a simple, example based and none-parameter method. But in the KNN algorithm, the fixed K value ignores the influence of the category and the document number of training text. So, selecting the correct K value can achieve better classification results. This paper proposes a kind of dynamic obtain k-valued for KNN classification algorithm, experimental results show that the dynamic obtain k-valued KNN classification algorithm with high performance.