Many decision tree (DT) induction algorithms, including the popular C4.5 family, are based on the Conditional Entropy (CE) measure family. An interesting question involves the relative performance of other entropy measure families such as Class-Attribute Mutual Information (CAMI). We therefore conducted a theoretical analysis of the CAMI family that enabled us to expose relationships with CE an...

The increased penetration of renewables in power distribution networks has motivated significant interest local energy systems. One the main goals markets is to promote participation small consumers transactions. Such transactions can be modeled as a bi-level optimization problem which players (e.g., consumers, prosumers, or producers) at upper level try maximize their profits, whereas market m...

We show that the energy averaged entropy localization length for the eigenstates of the Ce atom is well approximated by the prediction of the Wigner ensemble.

With increasing consumer expectations for the quality and safety of agricultural products, intelligent detection gradation have considerable significance in production. The surface defect is an important indicator quality, but classified mainly using inefficient manual identification “Yuluxiang” pears. Because uncertainty high difficulty image acquisition agriculture, data imbalance between cat...

ross-entropy is a measure of the difference between two distribution functions. In order to deal with the divergence of uncertain variables via uncertainty distributions, this paper aims at introducing the concept of cross-entropy for uncertain variables based on uncertain theory, as well as investigating some mathematical properties of this concept. Several practical examples are also provided...

Skull stripping has an important in neuroimaging workflow. is a time-consuming process the Magnetic resonance imaging (MRI). For this reason, skull and brain segmentation are aimed study. purpose, U-NET architecture design, which one of frequently used models field medical image segmentation, was used. Also, different loss functions such as Cross Entropy (CE), Dice, IoU, Tversky, Focal Tversky ...

In this study, we present new analytical metrics for evaluating the performance of side-channel attacks (SCAs) by revisiting perceived information (PI), which is defined using cross-entropy (CE). PI represents amount utilized a probability distribution that determines distinguishing rule in SCA. Our analysis partially solves an important open problem evaluation deep-learning based SCAs (DL-SCAs...

LAZY TRAINING: INTERACTIVE CLASSIFICATION LEARNING Michael Rimer Department of Computer Science Master of Science Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents the paradigm of Interactive Training (IT), a logical extension to backpropagation training of artificial neural networks that employs interaction...

Consider a network of unreliable links, each of which comes with a certain price and reliability. Given a fixed budget, which links should be bought in order to maximize the system’s reliability? We introduce a Cross-Entropy approach to this problem, which can deal effectively with the noise and constraints in this difficult combinatorial optimization problem. Numerical results demonstrate the ...