TY - GEN
T1 - A comparison of supervised learning techniques for clustering
AU - Ezekiel, William
AU - Thayasivam, Umashanger
N1 - Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - The significance of data mining has experienced dramatic growth over the past few years. This growth has been so drastic that many industries and academic disciplines apply data mining in some form. Data mining is a broad subject that encompasses several topics and problems; however this paper will focus on the supervised learning classification problem and discovering ways to optimize the classification process. Four classification techniques (naive Bayes, support vector machine, decision tree, and random forest) were studied and applied to data sets from the UCI Machine Learning Repository. A Classification Learning Toolbox (CLT) was developed using the R statistical programming language to analyze the date sets and report the relationships and prediction accuracy between the four classifiers.
AB - The significance of data mining has experienced dramatic growth over the past few years. This growth has been so drastic that many industries and academic disciplines apply data mining in some form. Data mining is a broad subject that encompasses several topics and problems; however this paper will focus on the supervised learning classification problem and discovering ways to optimize the classification process. Four classification techniques (naive Bayes, support vector machine, decision tree, and random forest) were studied and applied to data sets from the UCI Machine Learning Repository. A Classification Learning Toolbox (CLT) was developed using the R statistical programming language to analyze the date sets and report the relationships and prediction accuracy between the four classifiers.
UR - http://www.scopus.com/inward/record.url?scp=84952801834&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-26532-2_52
DO - 10.1007/978-3-319-26532-2_52
M3 - Conference contribution
AN - SCOPUS:84952801834
SN - 9783319265315
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 476
EP - 483
BT - Neural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings
A2 - Lai, Weng Kin
A2 - Liu, Qingshan
A2 - Huang, Tingwen
A2 - Arik, Sabri
PB - Springer Verlag
T2 - 22nd International Conference on Neural Information Processing, ICONIP 2015
Y2 - 9 November 2015 through 12 November 2015
ER -