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Mining Online Store Client Assessment Classification Rules with Genetic Algorithms

Mining Online Store Client Assessment Classification Rules with Genetic Algorithms

The paper presents the results of the research into algorithms that are not meant to mine classification rules, yet they contain all the necessary functions which allow us to use them for mining classification rules such as Genetic algorithm (GA). The main task of the research is associated with the application of GA to classification rule mining. A classic GA was modified to match the chosen classification task and was compared with other popular classification algorithms - JRip, J48 and Naive Bayes classifier. The paper describes the algorithm proposed and the application task as well as provides a comparative analysis of the obtained results with other algorithms.

Open access
Impact of Antibody Panel Size on Classification Accuracy

Impact of Antibody Panel Size on Classification Accuracy

This paper experimentally studies the influence of antibody panel size reduction on classification results. The presented study includes four classification methods and five feature evaluators that are applied to five different biomedical data sets with large dimensionality (1200 features). The behaviour of the classifiers in these data sets is examined to reveal overall trends of dimensionality reduction impact on classification accuracy.

Open access
Using Fuzzy Logic to Solve Bioinformatics Tasks

Using Fuzzy Logic to Solve Bioinformatics Tasks

The goal of this research is to investigate, collect and identify published methods that use fuzzy techniques in bioinformatics tasks. Special attention is paid to studying how the advantages of fuzzy techniques are used in various stages like preprocessing, optimization and building a classifier of classification task as difficult as processing microarray data. This article also inspects the most popular databases used in bioinformatics. The most perspective methods are given more detailed descriptions. Conclusions are made about working abilities of the algorithms and their use in further research.

Open access
Transportation Mode Choice Analysis Based on Classification Methods

Transportation Mode Choice Analysis Based on Classification Methods

Mode choice analysis has received the most attention among discrete choice problems in travel behavior literature. Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. This paper investigates performance of mode choice analysis with classification methods - decision trees, discriminant analysis and multinomial logit. Experimental results have demonstrated satisfactory quality of classification.

Open access
Decision Tree Classifiers in Bioinformatics

Decision Tree Classifiers in Bioinformatics

This paper presents a literature review of articles related to the use of decision tree classifiers in gene microarray data analysis published in the last ten years. The main focus is on researches solving the cancer classification problem using single decision tree classifiers (algorithms C4.5 and CART) and decision tree forests (e.g. random forests) showing strengths and weaknesses of the proposed methodologies when compared to other popular classification methods. The article also touches the use of decision tree classifiers in gene selection.

Open access
The Extraction of Elliptical Rules from the Trained Radial Basis Function Neural Network

Abstract

The paper describes an algorithm for approximation of trained radial basis function neural network (RBFNN) classification boundary with the help of elliptic rules. These rules can later be translated into IF-THEN form if required. We provide experimental results of the algorithm for a two-dimensional case. Currently, neural networks are not widely used and spread due to difficulties with the interpretation of classification decision being made. The formalized representation of decision process is required in many mission critical areas, such as medicine, nuclear energy, finance and others.

Open access
Influence of Membership Functions on Classification of Multi-Dimensional Data

Influence of Membership Functions on Classification of Multi-Dimensional Data

The aim of this study is to explore whether the number of intervals for each attribute influences the classification result and whether a larger number of intervals provide better classification accuracy using the Fuzzy PRISM algorithm. The feature selection has been carried out using Fast correlation-based filter solution, and then the decreased data sets have been applied in experiments with preferences used in the previous experiment series. The article also provides conclusions about the obtained classification results and analyzes criteria of certain experiments and their impact on the final result. Also a series of experiments was carried out to assess how and whether the classification result is influenced by categorization of continuous data, which is one of the membership function construction steps; Fuzzy unordered rule induction algorithm was used. The experiments have been carried out using four real data sets - Golub leukemia, Singh prostate, as well as Gastric cancer and leukemia donor data sets of the Latvian Biomedical Research and Study Center.

Open access
The Use of BEXA Family Algorithms in Bioinformatics Data Classification

Abstract

This article studies the possibilities of BEXA family classification algorithms - BEXA, FuzzyBexa and FuzzyBexa II in data, especially bioinformatics data, classification. Three different types of data sets have been used in the study - data sets often used in the literature, UCI data repository real life data sets and real bioinformatics data sets that have the specific character - a large number of attributes and a small number of records. For the comparison of classification results experiments have been carried out using all data sets and other classification algorithms. As a result, conclusions have been drawn and recommendations given about the use of each algorithm of BEXA family for classification of various real data, as well as an answer has been given to the question, whether the use of these algorithms is recommended for bioinformatics data.

Open access
A Review of Potentillo Ternatae — Nardion Strictae Alliance

A Review of Potentillo Ternatae — Nardion Strictae Alliance

A classification of the Nardus stricta dominated communities in the Balkan Range is presented. Two associations are identified: Nardetum strictae and Campanulo alpinae — Nardetum strictae nom. nov. The alliance Potentillo ternatae — Nardion strictae is typified and some comments on its distribution range and syntaxonomical affiliation to the higher units are presented. A synopsis is included of all available associations referred to Potentillo ternatae — Nardion strictae.

Open access
Conspectus of Vegetation Syntaxa in Slovenia

Conspectus of Vegetation Syntaxa in Slovenia

For the first time, an overview of plant communities in Slovenia is presented according to the Braun-Blanquet approach. In total 588 associations (and some communities classified into higher syntaxa) belonging to 51 classes have been registered in Slovenia. Additionally 149 syntaxa are mentioned as registered in the field or in, the literature, but not documented with relevé material. Syntaxonomical classification is based on the "EuroChecklist" and includes also the Slovenian written definition of the high-rank syntaxa.

Open access