Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan

ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF) in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withe...

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Main Authors: Senol Celik, Ecevit Eyduran, Koksal Karadas, Mohammad Masood Tariq
Format: Article
Language:English
Published: Sociedade Brasileira de Zootecnia
Series:Revista Brasileira de Zootecnia
Subjects:
ANN
Online Access:http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982017001100863&lng=en&tlng=en
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spelling doaj-4f4bfaf8aa9443bd947a7a1ddc0ae3542020-11-24T22:27:41ZengSociedade Brasileira de ZootecniaRevista Brasileira de Zootecnia1806-9290461186387210.1590/s1806-92902017001100005S1516-35982017001100863Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of PakistanSenol CelikEcevit EyduranKoksal KaradasMohammad Masood TariqABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF) in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth) and testicular (testicular length, scrotal length, and scrotal circumference) measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1) and with interaction (MARS_2) terms. The superiority order in the predictive accuracy of the algorithms was found as CART > CHAID ≈ Exhaustive CHAID > MARS_2 > MARS_1 > RBF > MLP. Moreover, all tested algorithms provided a strong predictive accuracy for estimating body weight. However, MARS is the only algorithm that generated a prediction equation for body weight. Therefore, it is hoped that the available results might present a valuable contribution in terms of predicting body weight and describing the relationship between the body weight and body and testicular measurements in revealing breed standards and the conservation of indigenous gene sources for Mengali sheep breeding. Therefore, it will be possible to perform more profitable and productive sheep production. Use of data mining algorithms is useful for revealing the relationship between body weight and testicular traits in describing breed standards of Mengali sheep.http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982017001100863&lng=en&tlng=enANNartificial intelligencedata miningdecision treeMARS algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Senol Celik
Ecevit Eyduran
Koksal Karadas
Mohammad Masood Tariq
spellingShingle Senol Celik
Ecevit Eyduran
Koksal Karadas
Mohammad Masood Tariq
Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan
Revista Brasileira de Zootecnia
ANN
artificial intelligence
data mining
decision tree
MARS algorithm
author_facet Senol Celik
Ecevit Eyduran
Koksal Karadas
Mohammad Masood Tariq
author_sort Senol Celik
title Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan
title_short Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan
title_full Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan
title_fullStr Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan
title_full_unstemmed Comparison of predictive performance of data mining algorithms in predicting body weight in Mengali rams of Pakistan
title_sort comparison of predictive performance of data mining algorithms in predicting body weight in mengali rams of pakistan
publisher Sociedade Brasileira de Zootecnia
series Revista Brasileira de Zootecnia
issn 1806-9290
description ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF) in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth) and testicular (testicular length, scrotal length, and scrotal circumference) measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1) and with interaction (MARS_2) terms. The superiority order in the predictive accuracy of the algorithms was found as CART > CHAID ≈ Exhaustive CHAID > MARS_2 > MARS_1 > RBF > MLP. Moreover, all tested algorithms provided a strong predictive accuracy for estimating body weight. However, MARS is the only algorithm that generated a prediction equation for body weight. Therefore, it is hoped that the available results might present a valuable contribution in terms of predicting body weight and describing the relationship between the body weight and body and testicular measurements in revealing breed standards and the conservation of indigenous gene sources for Mengali sheep breeding. Therefore, it will be possible to perform more profitable and productive sheep production. Use of data mining algorithms is useful for revealing the relationship between body weight and testicular traits in describing breed standards of Mengali sheep.
topic ANN
artificial intelligence
data mining
decision tree
MARS algorithm
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1516-35982017001100863&lng=en&tlng=en
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AT koksalkaradas comparisonofpredictiveperformanceofdataminingalgorithmsinpredictingbodyweightinmengaliramsofpakistan
AT mohammadmasoodtariq comparisonofpredictiveperformanceofdataminingalgorithmsinpredictingbodyweightinmengaliramsofpakistan
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