@Article{2019.100000153,
AUTHOR = {Uma K.V, Appavu alias Balamurugan S},
TITLE = {C5.0 Decision Tree Model Using Tsallis Entropy and Association Function  for General and Medical Dataset},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {26},
YEAR = {2020},
NUMBER = {1},
PAGES = {61--70},
URL = {http://www.techscience.com/iasc/v26n1/39858},
ISSN = {2326-005X},
ABSTRACT = {Real world data consists of lot of impurities. Entropy measure will help to 
handle impurities in a better way. Here, data selection is done by using Naïve 
Bayes’ theorem. The sample which has posterior probability value greater than 
that of the threshold value is selected. C5.0 decision tree classifier is taken as 
base and modified the Gain calculation function using Tsallis entropy and 
Association function. The proposed classifier model provides more accuracy and 
smaller tree for general and Medical dataset. Precision value obtained for 
Medical dataset is more than that of existing method.},
DOI = {10.31209/2019.100000153}
}