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To improve the accuracy of clustering classification the Adaptive Genetic Algorithm was proposed. The code is float, the selection operator is rank-based fitness assignment and elitist model, the crossover operator is real valued recombination, the mutation operator is real mutation. The adaptive crossover probability and adaptive mutation probability are proposed, which consider the influence of...
Microarray gene expression data is voluminous and very few genes in the dataset are informative for disease analysis. Selecting those genes from the whole dataset is a very challenging task. There are many optimization techniques used by the researchers for gene subset selection but none of them provides global optimal solution for all gene datasets. In the paper, we have proposed a strength pareto...
Cluster analysis being one of the important techniques of data mining applied in several fields such as bioinformatics, social networks, computer vision, and so on. It is an unsupervised learning technique for exploring the structure of the data without class label. Many clustering algorithms have been proposed to analyze high volume of data, but very few of them evaluate the quality of the clusters...
This paper proposes a new method for partitioning data clustering using PSO. The Proposed methods LPSOC designed for hard clusters. LPSOC alleviate some of the drawbacks of traditional algorithms and the state-of-the-art PSO clustering algorithm. Population-based algorithms such as PSO is less sensitive to initial condition than other algorithms such as K-means since search starts from multiple positions...
Cluster analysis is an important task almost in all fields including bioinformatics, social networks, agriculture, and so on. It basically explores the natural structure of the data without any prior knowledge about it. In many real data sets, the objects reside in many clusters with different membership values. Many clustering algorithms have been proposed for finding such overlapping clusters to...
This paper presents a two-stage approach for reconstruction of cross-cut shredded text documents. Cross-cut shredding is used to mechanically cut a document into rectangular shreds of (almost) identical shapes. After pre-processing shreds with image-based techniques, we defined a cluster quality measure called "matching proportion" (MP), with which, shreds in the same rows were found by...
The genetic algorithm with greedy heuristic, initially developed for solving location problems on networks, can be adapted for solving continuous problems such as k-means. However, the efficiency of such algorithm in case of continuous problems does not allow to use it for solving the large-scale problems. In this paper, authors propose a modification to this algorithm which allows such algorithm...
This paper analyses and studies genetic algorithm and classical clustering algorithms, and then the demand analysis and design of the personnel management system of Shenyang Administration College. The adaptive crossover probability and adaptive mutation probability are proposed, which consider the influence of every generation to algorithm and the effect of different individual fitness in every generation...
The estimation of the number of clusters (NC) is one of crucial problems in the cluster analysis of gene expression data. Most approaches available give their answers without the intuitive information about separable degrees between clusters. However, this information is useful for understanding cluster structures. To provide this information, we propose system evolution (SE) method to estimate NC...
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