PREDIKSI TERJANGKITNYA PENYAKIT JANTUNG DENGAN METODE LEARNING VECTOR QUANTIZATION

Hidayati, Nurul and Warsito, Budi (2010) PREDIKSI TERJANGKITNYA PENYAKIT JANTUNG DENGAN METODE LEARNING VECTOR QUANTIZATION. Media Statistika, 3 (1). pp. 21-30. ISSN 1979-3693

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Abstract

Learning Vector Quantization (LVQ) is a method that train the competitives layer with supervised. The competitives layer will learn automatically to classify the input vector given. If some input vectors has the short distance then the input vector will be grouped into the same class. The LVQ method can be used to classify the data into some classes or categories. At this paper, the LVQ method will be applied to classify if someone is suffer potenciate of heart desease or not. The data that be trained are 268 data of heart desease patient from UCI (University of California at Irvine) with 10 variables that are factors influence that infected of heart desease. From some trials showed that the learning rate (α) = 0.25, decrease of learning rate (Decα) = 0.1, and the minimum learning rate (Minα) = 0.001 are values that give a good prediction with level of accuracy is about 66.79 %. Keywords: Learning Vector Quantization, Classify, Heart Desease

Item Type:Article
Subjects:Q Science > Q Science (General)
Divisions:Faculty of Science and Mathematics > Department of Statistics
ID Code:32969
Deposited By:Mr Hasbi Yasin
Deposited On:06 Feb 2012 09:40
Last Modified:06 Feb 2012 09:40

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