Displaying similar documents to “New machine learning methods for prediction of protein secondary structures”

Knowledge discovery in data using formal concept analysis and random projections

Cherukuri Aswani Kumar (2011)

International Journal of Applied Mathematics and Computer Science

Similarity:

In this paper our objective is to propose a random projections based formal concept analysis for knowledge discovery in data. We demonstrate the implementation of the proposed method on two real world healthcare datasets. Formal Concept Analysis (FCA) is a mathematical framework that offers a conceptual knowledge representation through hierarchical conceptual structures called concept lattices. However, during the design of a concept lattice, complexity plays a major role.

Genetic Algorithm Approach for Solving the Task Assignment Problem

Savić, Aleksandar, Tošić, Dušan, Marić, Miroslav, Kratica, Jozef (2008)

Serdica Journal of Computing

Similarity:

This research was partially supported by the Serbian Ministry of Science and Ecology under project 144007. The authors are grateful to Ivana Ljubić for help in testing and to Vladimir Filipović for useful suggestions and comments. In this paper a genetic algorithm (GA) for the task assignment problem (TAP) is considered.An integer representation with standard genetic operators is used. Computational results are presented for instances from the literature, and compared to...

Solving the Task Assignment Problem with a Variable Neighborhood Search

Kratica, Jozef, Savić, Aleksandar, Filipović, Vladimir, Milanović, Marija (2010)

Serdica Journal of Computing

Similarity:

In this paper a variable neighborhood search (VNS) approach for the task assignment problem (TAP) is considered. An appropriate neighborhood scheme along with a shaking operator and local search procedure are constructed specifically for this problem. The computational results are presented for the instances from the literature, and compared to optimal solutions obtained by the CPLEX solver and heuristic solutions generated by the genetic algorithm. It can be seen that the proposed...

A comparative evaluation of medium- and large-scale feature selectors for pattern classifiers

Mineichi Kudo, Jack Sklansky (1998)

Kybernetika

Similarity:

Needs of feature selection in medium and large problems increases in many fields including medical and image processing fields. Previous comparative studies of feature selection algorithms are not satisfactory in problem size and in criterion function. In addition, no way has not shown to compare algorithms with different objectives. In this study, we propose a unified way to compare a large variety of algorithms. Our results show that the sequential floating algorithms promises for...

Weighting quantitative and qualitative variables in clustering methods.

Karina Gibert, Ulises Cortés (1997)

Mathware and Soft Computing

Similarity:

Description of individuals in ill-structured domains produces messy data matrices. In this context, automated classification requires the management of those kind of matrices. One of the features involved in clustering is the evaluation of distances between individuals. Then, a special function to calculate distances between individuals partially simultaneously described by qualitative and quantitative variables is required. In this paper properties and details of the metrics...