نتایج جستجو برای: rule weighting

تعداد نتایج: 175478  

2013
M. TAHERI H. AZAD K. ZIARATI R. SANAYE

Recently, tuning the weights of the rules in Fuzzy Rule-Base Classification Systems is researched in order to improve the accuracy of classification. In this paper, a margin-based optimization model, inspired by Support Vector Machine classifiers, is proposed to compute these fuzzy rule weights. This approach not only considers both accuracy and generalization criteria in a single objective fun...

2014
Ranka Kulić

The problem of path generation for the autonomous vehicle in environments with infinite number obstacles is considered. Generally, the problem is known in the literature as the path planning. This chapter treated that problem using the algorithm, named MKBC, which is based on the behavioral cloning and Kohonen rule. In the behavioral cloning, the system learns from control traces of a human ope...

2004
Branko Kavšek Nada Lavrač

This paper investigates the implications of example weighting in subgroup discovery by comparing three state-of-the-art subgroup discovery algorithms, APRIORI-SD, CN2-SD, and SubgroupMiner on a real-life data set. While both APRIORI-SD and CN2-SD use example weighting in the process of subgroup discovery, SubgroupMiner does not. Moreover, APRIORI-SD uses example weighting in the post-processing...

2013
Niko Brümmer George R. Doddington

Prior-weighted logistic regression has become a standard tool for calibration in speaker recognition. Logistic regression is the optimization of the expected value of the logarithmic scoring rule. We generalize this via a parametric family of proper scoring rules. Our theoretical analysis shows how different members of this family induce different relative weightings over a spectrum of applicat...

2009
Young Im CHO

A fuzzy control system which is a typical system utilizing fuzzy model is mainly using the Max-Min CRI (Compositional Rule of Inference) method by Zadeh and Mamdani for fuzzy inference. But the Max-Min CRI method suffers from drawbacks including: error-prone weighting strategy, inefficient compositional rule of inference, and subjective formulation of membership functions. Because of these prob...

2004
Engin Erzin Yücel Yemez A. Murat Tekalp

We present a multimodal open-set speaker identification system that integrates information coming from audio, face and lip motion modalities. For fusion of multiple modalities, the so called product rule with a novel adaptive reliability based weighting structure is employed. The proposed adaptive product rule is more robust in the presence of unreliable modalities, provided that the employed r...

2005
Qijun Chen Xindong Wu Xingquan Zhu

With the rapid advancement of information technology, scalability has become a necessity for learning algorithms to deal with large, real-world data repositories. In this paper, scalability is accomplished through a data reduction technique, which partitions a large data set into subsets, applies a learning algorithm on each subset sequentially or concurrently, and then integrates the learned r...

1996
Robin R. Murphy

Landmark-based navigation of autonomous mobile robots require the integration of observations from sensors over time. This paper shows that Dempster's rule of combination is not appropriate for this domain. An alternative rule of combination for Shafer belief functions is derived, which adapts the belief updating process based on a contextual weighting parameter, n. n is a function of the expec...

1996
Nicklas Ekstrand

In this article we report on a study of how to use the context tree weight-ing (CTW) algorithm for lossless image compression. This algorithm has been shown to perform optimally, in terms of redundancy, for a wide class of data sources. Our study shows that this algorithm can successfully be applied to image compression even in its basic form. We also report on possible modiica-tions of the bas...

Journal: :Inf. Sci. 2014
Andri Riid Ennu Rüstern

This paper discusses interpretability in two main categories of fuzzy systems fuzzy rule-based classifiers and interpolative fuzzy systems. Our goal is to show that the aspect of high level interpretability is more relevant to fuzzy classifiers, whereas fuzzy systems employed in modeling and control benefit more from low-level interpretability. We also discuss the interpretabilityaccuracy trade...

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