Comparative Analysis of Various Decision Tree Classification Algorithms using WEKA
P. Sharma. International Journal on Recent and Innovation Trends in Computing and Communication, 3 (2):
684--690(Februar 2015)
DOI: 10.17762/ijritcc2321-8169.150254
Zusammenfassung
Classification is a technique to construct a function or set of functions to predict the class of instances whose class label is not known. Discovered knowledge is usually presented in the form of high level, easy to understand classification rules. There is various classification techniques used to classify the data, one of which is decision tree algorithms. This paper presents a comparative analysis of various decision tree based classification algorithms. In experiments, the effectiveness of algorithms is evaluated by comparing the results on 5 datasets from the UCI and KEEL repository
%0 Journal Article
%1 Sharma_2015
%A Sharma, Priyanka
%D 2015
%I Auricle Technologies, Pvt., Ltd.
%J International Journal on Recent and Innovation Trends in Computing and Communication
%K classification data decision mining tree weka
%N 2
%P 684--690
%R 10.17762/ijritcc2321-8169.150254
%T Comparative Analysis of Various Decision Tree Classification Algorithms using WEKA
%U http://dx.doi.org/10.17762/ijritcc2321-8169.150254
%V 3
%X Classification is a technique to construct a function or set of functions to predict the class of instances whose class label is not known. Discovered knowledge is usually presented in the form of high level, easy to understand classification rules. There is various classification techniques used to classify the data, one of which is decision tree algorithms. This paper presents a comparative analysis of various decision tree based classification algorithms. In experiments, the effectiveness of algorithms is evaluated by comparing the results on 5 datasets from the UCI and KEEL repository
@article{Sharma_2015,
abstract = {Classification is a technique to construct a function or set of functions to predict the class of instances whose class label is not known. Discovered knowledge is usually presented in the form of high level, easy to understand classification rules. There is various classification techniques used to classify the data, one of which is decision tree algorithms. This paper presents a comparative analysis of various decision tree based classification algorithms. In experiments, the effectiveness of algorithms is evaluated by comparing the results on 5 datasets from the UCI and KEEL repository},
added-at = {2015-08-04T08:03:27.000+0200},
author = {Sharma, Priyanka},
biburl = {https://www.bibsonomy.org/bibtex/2501a3caf7ecd43275cb81188e93decb4/ijritcc},
doi = {10.17762/ijritcc2321-8169.150254},
interhash = {b162adf0a1a7896a79b5bdd1b760d5a1},
intrahash = {501a3caf7ecd43275cb81188e93decb4},
journal = {International Journal on Recent and Innovation Trends in Computing and Communication},
keywords = {classification data decision mining tree weka},
month = {february},
number = 2,
pages = {684--690},
publisher = {Auricle Technologies, Pvt., Ltd.},
timestamp = {2015-08-04T08:03:27.000+0200},
title = {Comparative Analysis of Various Decision Tree Classification Algorithms using {WEKA}},
url = {http://dx.doi.org/10.17762/ijritcc2321-8169.150254},
volume = 3,
year = 2015
}