یک الگوریتم انتخاب ویژگی برخط گروهی با استفاده از نظریه اطلاعات متقابل
الموضوعات : سامانه‌های پردازشی و ارتباطی چندرسانه‌ای هوشمندمریم رحمانی نیا 1 , سندس بهادری 2
1 - 1. استادیار، گروه کامپیوتر، مرکز قصرشیرین، دانشگاه آزاد اسلامی، قصرشیرین، ایران
2 - 2. استادیار، گروه کامپیوتر، واحد ایلام، دانشگاه آزاد اسلامی، ایلام، ایران
الکلمات المفتاحية: الگوریتم‌های انتخاب ویژگی گروهی برخط, داده‌های با جریان برخط, اطلاعات متقابل,
ملخص المقالة :
امروزه ویژگی ها به صورت پیوسته و یکی یکی یا گروهی به مجموعه داده ها اضافه می شوند. این امر باعث افزایش بی رویه ابعاد داده های آموزشی می شود. روش های انتخاب ویژگی برخط، با انتخاب یک زیر مجموعه مهم از میان مجموعه ویژگی های دیده شده تا آن لحظه اندازه داده های آموزشی را کاهشمی دهند و در نتیجه عملکرد الگوریتم های یادگیری ماشین را بهبود می بخشند. اما به دلیل عدم قطعیت و ابهام در داده های آموزشی، روش های انتخاب ویژگی برخط موجود معمولاً از مشکلاتی مانند مقیاس پذیری، دقت پایین و زمان اجرای بالا رنج می برند. همچنین بسیاری از این روش ها توانایی انتخاب ویژگی های مهم هنگامی که ویژگی ها به صورت گروهی به مجموعه داده ها اضافه می شوند را ندارند. بنابراین در این مقاله، یک روش انتخاب ویژگی برخط گروهی بر اساس نظریه اطلاعات متقابل ارائه داده ایم. در روش پیشنهادی در ابتدا مقدار ارتباط هر یک از ویژگی های موجود در گروه تازه وارد شناسایی و سپس مقدار افزونگی ویژگی های انتخابی در گروه تازه وارد و مجموعه ویژگی هایی که قبلاً انتخاب شده محاسبه و ویژگی های اضافی حذف می شوند. نتایج به دست آمده توسط الگوریتم پیشنهادی در مقایسه با 3 الگوریتم انتخاب ویژگی برخط گروهی دیگر ارزیابی شده است. طبق نتایج حاصل، الگوریتم پیشنهادی کارایی بالاتری نسبت به سایر الگوریتم ها به دست آورده است.
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