This paper surveys the machine learning literature and presents in an optimization
framework several commonly used machine learning approaches. Particularly …

We study problems of optimization of decision and inhibitory trees for decision tables with
many-valued decisions. As cost functions, we consider depth, average depth, number of …

This paper develops an integrated machine learning and enhanced statistical approach for
wind power interval forecasting. A time‐series wind power forecasting model is formulated …

Decision tree is a widely used technique to discover patterns from consistent data set. But if
the data set is inconsistent, where there are groups of examples (objects) with equal values …

Decision trees are one of the most commonly used tools in decision analysis, knowledge
representation, machine learning, etc., for its simplicity and interpretability. We consider an …

In this chapter, we study bi-criteria optimization problem cost versus cost for decision and
inhibitory trees. We design an algorithm which constructs the set of Pareto optimal points for …

منصة المنهل لقد انتهت الجلسة. يرجى العمل على إعادة تحديث الصفحة إعادة تحديث يرجى الانتظار...
يتم تحضير الملف الاستخدام المجاني إذا كنت ترغب في الوصول الكامل إلى هذا المحتوى وقاعدة …‎

요 약미세먼지 농도별 특성에 따라 예측 모델의 학습이 잘 이루어지지 않는 문제가 있다. 이러한
문제를해결하기 위해 저농도와 고농도에 대한 예측 모델을 구분하여 설계할 필요가 있다 …