<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1405-5546</journal-id>
<journal-title><![CDATA[Computación y Sistemas]]></journal-title>
<abbrev-journal-title><![CDATA[Comp. y Sist.]]></abbrev-journal-title>
<issn>1405-5546</issn>
<publisher>
<publisher-name><![CDATA[Instituto Politécnico Nacional, Centro de Investigación en Computación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-55462018000401625</article-id>
<article-id pub-id-type="doi">10.13053/cys-22-4-2602</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Functional Expansions Based Multilayer Perceptron Neural Network for Classification Task]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Iqbal]]></surname>
<given-names><![CDATA[Umer]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Ghazali]]></surname>
<given-names><![CDATA[Rozaida]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mushtaq]]></surname>
<given-names><![CDATA[Muhammad Faheem]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Kanwal]]></surname>
<given-names><![CDATA[Afshan]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,University Tun Hussein Onn Malaysia Faculty of Computer Science and Information Technology ]]></institution>
<addr-line><![CDATA[Johor ]]></addr-line>
<country>Malaysia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,University Pakistan Riphah College of Computing Riphah International ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Malaysia</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,University Tun Hussein Onn Malaysia Department of Mathematics and Statistics ]]></institution>
<addr-line><![CDATA[Johor ]]></addr-line>
<country>Malaysia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2018</year>
</pub-date>
<volume>22</volume>
<numero>4</numero>
<fpage>1625</fpage>
<lpage>1635</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462018000401625&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462018000401625&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462018000401625&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Artificial neural network has been proved among the best tools in data mining for classification tasks. Where, Multilayer Perceptron (MLP) is known as benchmarked technique for classification tasks due to common use and easy implementation. Meanwhile, it is fail to make high combination of inputs from lower feature space to higher feature space. In this paper, Shifted Genocchi polynomials and Chebyshev Wavelets functional expansions based Multilayer Perceptron techniques with Levenberg Marquardt back propagation learning are proposed to deal with high dimension problems in classification tasks. Five datasets from UCI repository and KEEL datasets were collected to evaluate the performance in terms of five evaluation measures. T-test was applied to check the significance of the proposed techniques. The comparison results show that the proposed models outperform in terms of accuracy, sensitivity, specificity, precision and f-measure.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Data mining]]></kwd>
<kwd lng="en"><![CDATA[classification]]></kwd>
<kwd lng="en"><![CDATA[shifted Genocchi polynomials]]></kwd>
<kwd lng="en"><![CDATA[Chebyshev wavelets]]></kwd>
<kwd lng="en"><![CDATA[multilayer perceptron]]></kwd>
</kwd-group>
</article-meta>
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