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<journal-id journal-id-type="publisher">global-journal-of-computer-science-and-technology-c-software-data-engineering</journal-id>
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<journal-title>Global Journal of Computer Science and Technology - C: Software &amp; Data Engineering</journal-title>
</journal-title-group>
<issn publication-format="print">0975-4350</issn>
<issn publication-format="electronic">0975-4172</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
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<article-id pub-id-type="publisher-id">115943</article-id>
<title-group>
<article-title>Analysis of Heart Disease using in Data Mining Tools Orange and Weka</article-title>
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<contrib-group>
<contrib contrib-type="author"><name><surname>Kodati</surname><given-names>Sarangam</given-names></name><xref ref-type="aff" rid="aff1" />
</contrib>
</contrib-group>
<aff id="aff1">INDIA, Sri Satya Sai University of Technology and Medical Science</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2018-01-15">
<day>15</day>
<month>01</month>
<year>2018</year>
</pub-date>
<volume>18</volume>
<issue>C1</issue>
<abstract><p>Health care is an inevitable task to be done in human life. Health concern business has become a notable field in the wide spread area of medical science. Health care industry contains large amount of data and hidden information. Effective decisions are made with this hidden information by applying patient; however, with data mining these tests could be reduced. But there is a lack of analyzing tool according to provide effective test outcomes together with the hidden information, so and such system is developed using data mining algorithms for classifying the data and to detect the heart diseases. Data mining acts so a solution by many healthcare problems. Naïve Bayes, SVM, Random Forest, KNN algorithm is one such data mining method which serves with the diagnosis regarding heart diseases patient. This paper analyzes few parameters and predicts heart diseases, thereby suggests a heart diseases prediction system (HDPS) based total on the data mining approaches</p></abstract>
<kwd-group kwd-group-type="author-generated">
<kwd>data mining</kwd>
<kwd>weka</kwd>
<kwd>orange</kwd>
<kwd>heart disease</kwd>
<kwd>data mining classification techniques.</kwd>
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<p>Health care is an inevitable task to be done in human life. Health concern business has become a notable field in the wide spread area of medical science. Health care industry contains large amount of data and hidden information. Effective decisions are made with this hidden information by applying patient; however, with data mining these tests could be reduced. But there is a lack of analyzing tool according to provide effective test outcomes together with the hidden information, so and such system is developed using data mining algorithms for classifying the data and to detect the heart diseases. Data mining acts so a solution by many healthcare problems. Naïve Bayes, SVM, Random Forest, KNN algorithm is one such data mining method which serves with the diagnosis regarding heart diseases patient. This paper analyzes few parameters and predicts heart diseases, thereby suggests a heart diseases prediction system (HDPS) based total on the data mining approaches</p>
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