Different learning algorithms for the decision fusion mapping of a multiple classifier system are compared in this paper. It is very well known that the confusion matrices of the individual classifiers are utilised in the naive Bayes combination of classifier outputs. After a brief review of the decision templates, the linear associative memory and the pseudoinverse matrix approaches it is demo...

A rough set approach for attribute reduction is an important research subject in data mining and machine learning. However, most attribute reduction methods are performed on a complete decision system table. In this paper, we propose methods for attribute reduction in static incomplete decision systems and dynamic incomplete decision systems with dynamically-increasing and decreasing conditiona...

Pairwise comparison matrix as a crucial component of AHP, presents the preference relations among alternatives. However, in many cases, the pairwise comparison matrix is difficult to complete, which obstructs the subsequent operations of the classical AHP. In this paper, based on DEMATEL which has ability to derive the total relation matrix from direct relation matrix, a new completion method f...

In this paper we want to further investigate the usage of matrices as a representation of relations within arbitrary heterogeneous relation algebras. First, we want to show that splittings do exist in matrix algebras assuming that the underlying algebra of the coefficients provides this operation. Second, we want to outline an implementation of matrix algebras using reduced ordered multi-valued...

Generating discernibility matrix consumes huge time and space .To solve this problem, A new Binary Discernibility Matrix (BDM) induced from information table is defined, The concept of Binary Conjunction Matrix(BCM) is then introduced, Finally A novel method for discernibility matrix using Zero-Suppressed BDDs (ZBDD) and Ordered binary decision diagrams (OBDD) is proposed in this paper, experim...

Generating discernibility matrix consumes huge time and space .To solve this problem, A new Binary Discernibility Matrix (BDM) induced from information table is defined, The concept of Binary Conjunction Matrix(BCM) is then introduced, Finally A novel method for discernibility matrix using Ordered binary decision diagrams(OBDD) is proposed in this paper, experiment is carried to compare the sto...

In the speech recognition, a mandarin syllable wave is compressed into a matrix of linear predict coding cepstra (LPCC), i.e., a matrix of LPCC represents a mandarin syllable. We use the Bayes decision rule on the matrix to identify a mandarin syllable. Suppose that there are K different mandarin syllables, i.e., K classes. In the pattern classification problem, it is known that the Bayes decis...

This study proposes some issues to solve the Incomplete Linguistic Preference Relations under Multi-Criteria Decision Making. The proposed method has simple calculation and can speed up the process of comparison and selection of alternative. Experts obtain the matrix by choosing a finite and fixed set of alternatives and perform a pairwise comparison based on their different preferences and kno...

Just like matrix Chernoff bounds were a generalization of scalar Chernoff bounds, the multiplicative weights algorithm can be generalized to matrices. Recall that in the setup for the multiplicative weight update algorithm, we had a sequence of time steps t = 1, . . . , T ; in each time step t, we made a decision i ∈ {1...N} and got a value vt(i) ∈ [0, 1]. After we made a decision in time step ...

Pairwise comparison (PC) matrices are used in multi-attribute decision problems (MADM) in order to express the preferences of the decision maker. Our research focused on testing various characteristics of PC matrices. In a controlled experiment with university students (N = 227) we have obtained 454 PC matrices. The cases have been divided into 18 subgroups according to the key factors to be an...