IRDDS: Instance reduction based on Distance-based decision surface
نویسنده
چکیده مقاله:
In instance-based learning, a training set is given to a classifier for classifying new instances. In practice, not all information in the training set is useful for classifiers. Therefore, it is convenient to discard irrelevant instances from the training set. This process is known as instance reduction, which is an important task for classifiers since through this process the time for classification or training could be reduced. Instance-based learning methods are often confronted with the difficulty of choosing the instances which must be stored to be used during an actual test. Storing too many instances may result in large memory requirements and slow execution speed. In this paper, first, a Distance-based Decision Surface (DDS) is proposed which is used as a separating surface between the classes, then an instance reduction method, which is based on the DDS surface is proposed, namely IRDDS (Instance Reduction based on Distance-based Decision Surface). Using the DDS surface with Genetic algorithm selects a reference set for classification. IRDDS selects the most representative instances, satisfying both following objectives: high accuracy and reduction rates. The performance of IRDDS has been evaluated on real world data sets from UCI repository by the 10-fold cross-validation method. The results of the experiments are compared with some state-of-the-art methods, which show the superiority of the proposed method over the surveyed literature, in terms of both classification accuracy and reduction percentage.
منابع مشابه
irdds: instance reduction based on distance-based decision surface
in instance-based learning, a training set is given to a classifier for classifying new instances. in practice, not all information in the training set is useful for classifiers. therefore, it is convenient to discard irrelevant instances from the training set. this process is known as instance reduction, which is an important task for classifiers since through this process the time for classif...
متن کاملmortality forecasting based on lee-carter model
over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...
15 صفحه اولconstructing gender identity through narratives based on hallidays metafunctions
هویت, شکل دادن و بازنمایی آن در گفتمان, توجه بسیاری از محققان این رشته را به خود جلب کرده است. تحقیق حاضر بر شکل دادن به هویت جنسیتی هشت تن از دانشجویان ایرانی مشغول به تحصیل در دوره کارشناسی ارشد از طریق بررسی روایات آنان از تجربیات شخصی, متمرکز شده است. تحلیل داده ها در این تحقیق مشتمل بر سه بخش است: بخش اول شامل کدگذاری موضوعی روایات است که بر اساس آن هویت جنسیتی شرکت کنندگان در تحقیق بر اسا...
15 صفحه اولInstance-based learning in dynamic decision making
This paper presents a learning theory pertinent to dynamic decision making (DDM) called instancebased learning theory (IBLT). IBLT proposes five learning mechanisms in the context of a decision-making process: instance-based knowledge, recognition-based retrieval, adaptive strategies, necessity-based choice, and feedback updates. IBLT suggests in DDM people learn with the accumulation and refin...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ذخیره در منابع من قبلا به منابع من ذحیره شده{@ msg_add @}
عنوان ژورنال
دوره 3 شماره 2
صفحات 121- 130
تاریخ انتشار 2015-10-01
با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023