id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
work_dud6jcho45havihrl4d6i4z6iu	Fan Huimin	An Ensemble Learning Method for Text Classification Based on Heterogeneous Classifiers	2018	5	.pdf	application/pdf	2620	300	49	An Ensemble Learning Method for Text Classification Based on Heterogeneous obtain a diversity of base classifiers only through sample classification ensemble learning method based on multi-angle learning model has higher classification accuracy. learning method based on multi-angle perturbation classification results to integrate the classifiers. algorithms are ensemble learning based on homogenous heterogeneous classifiers can improve model classification accuracy of base classifiers and integrated models, and then integration model of the heterogeneous base classifier ENSEMBLE LEARNING MODEL BASED ON higher accuracy, more base classifiers with more diversity For each classification model, its algorithm parameters, an integrated learning model based on multi-angle B. The effect of feature selection algorithm and classifiers perturbation integrated model, only one of the classifiers can algorithm, feature dimension, classifier and its parameters integrated model based on multi-angle perturbation results show that the integrated learning model based on classification accuracy and rich base classifier diversity.	./cache/work_dud6jcho45havihrl4d6i4z6iu.pdf	./txt/work_dud6jcho45havihrl4d6i4z6iu.txt