An Algorithm of Incremental Bayesian Classifier Based on K-Nearest Neighbor
Dong Wang, Shi Huan Xiong · Advanced materials research · 2011
The learning sequence is an important factor of affecting the study effect about incremental Bayesian classifier. Reasonable learning sequence helps to strengthen the knowledge reserve of the classifier. This article proposes an incremental learning algorithm based on the K-Nearest Neighbor. Through calculating k maximum similar distance between test set and training set ,dividing and structuring the sequence of class number and the sequence of sum of class weight. According to the undulation degree of sequence, the instance including stronger class information is chosen to enter the learning process firstly. The experimental result indicates that the algorithm is effective and feasible.