Research on Incremental Learning of DragPush-Based Text Classification
Luo Changsheng · Zhongwen xinxi xuebao · 2008
The ability to incrementally learn from batches of data is an important feature that makes a learning algorithm more applicable to real-world problems.Incremental learning may be used to keep memory and time consumption of the learning algorithm at a manageable level.Incremental learning algorithms have been widely used for solving large-scale dataset problems.For text classification problem,the paper presents the general issues of an incremental learning algorithm.Based on DragPush strategy,the paper introduces a text classification incremental learning method,named ICCDP.Finally,it explores the issues of incremental learning based on ICCDP.The results of the experiment reveals that ICCDP is of high value for its fast training and its excellent classification performance.