Title :
Research of Text Categorization Model based on Random Forests
Author :
Dashen Xue ; Fengxin Li
Author_Institution :
Transp. & Manage. Dept., Dalian Maritime Univ., Dalian, China
Abstract :
Due to the good performance in computation speed and efficiency, Random Forest (RF) algorithm as a famous integrated learning algorithm has been widely applied in many fields. In addition, because of the rapid development of Internet, text categorization has become the key technology to process and organize large scale documents. It is appealing and important to employ RF algorithm to deal with text documents categorization problem. This paper introduces the details of RF algorithm and assess the text documents categorization model by using RF algorithm.
Keywords :
Internet; learning (artificial intelligence); text analysis; Internet; RF algorithm; integrated learning algorithm; large scale documents; random forest algorithm; text documents categorization model; text documents categorization problem; Algorithm design and analysis; Bagging; Decision trees; Radio frequency; Support vector machine classification; Text categorization; Training; Decision Tree; Random Forests; Text Categorization;
Conference_Titel :
Computational Intelligence & Communication Technology (CICT), 2015 IEEE International Conference on
Conference_Location :
Ghaziabad
Print_ISBN :
978-1-4799-6022-4
DOI :
10.1109/CICT.2015.101
