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
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
