رویکرد شورای انتخاب ویژگی بر اساس خوشه‌بندی سلسله‌مراتبی برای حل مشکل داده‌های زايد در بینی الکترونیکی
الموضوعات :
محمدعلی باقری
1
,
غلامعلی منتظر
2
1 - دانشگاه تربیت مدرس
2 - دانشگاه تربیت مدرس
الکلمات المفتاحية: بینی الکترونیکی خوشه‌بندی سلسله‌مراتبی سیستم دسته‌بند چندگانه شورای انتخاب ویژگی,
ملخص المقالة :
وجود داده‌هاي زايد در پاسخ حس‌گرهای بيني الكترونيكي اثر چشم‌گیری در دسته‌بندی بو دارد. برای بهبود صحت دسته‌بندی، می‌توان از سیستم دسته‌بندی چندگانه بر اساس انتخاب چند زیرمجموعه از ویژگی‌ها (به‌جای استفاده از تمام ابعاد بردار ویژگی) استفاده کرد. در این رویکرد که "شورای انتخاب ویژگی" نامیده می‌شود، فرض بر آن است که مجموعه اولیه ویژگی‌ها دارای داده‌هایی زايد بوده و می‌توان با انتخاب زیرمجموعه‌های ویژگی مختلف و سپس ترکیب دسته‌بندهای ایجادشده با این زیرمجموعه‌ها به نتایج دسته‌بندی بهتری رسید. در این مقاله پس از پیش‌پردازش سیگنال اولیه حس‌گرها و حذف نویز سیگنال با استفاده از تحلیل موجک، سیستم دسته‌بند چندگانه با زیرمجموعه‌های ویژگی مختلف طراحی شده است: ویژگی‌های استخراج‌شده از سیگنال گذرای حس‌گر با روش خوشه‌بندی سلسله‌مراتبی طبقه‌بندی شده و زیرمجموعه‌های مختلف با انتخاب یک ویژگی از هر خوشه ایجاد شده‌اند. این موضوع موجب بهبود تنوع دسته‌بندهای پایه و افزایش کارایی و سرعت دسته‌بندی می‌شود. روش پیشنهادی ابتدا در چند مجموعه داده تراز از مخزن داده UCI آزمون شده و پس از اثبات توانایی آن، در مجموعه داده بویایی حاصل از رایحه سه نوع شیرین‌بیان به کار برده شده است. نتایج حاصل نشان‌دهنده کارایی روش جدید در شناسایی الگوهای بویایی است.
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