SVM based methods for arrhythmia classification in ECG
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In this section we will propose a method to compress the impulse-response sample space based on k -nearest neighbors algorithm. In this sample space the number of
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Kategori data uji tidak sama dengan data latih menunjukkan hasil klasifikasi 66,67% untuk kondisi atrial fibrilation, 75% untuk kondisi ventricular tachycardia, 40% untuk
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