Comparison of different Clustering Algorithms for Gene Prediction
نویسنده
چکیده
1 Student M.Tech. (CSE), 2 Assistant Professor 1,2 Departmnet of Computer Science and Engineering, GNDU Regional Campus, Gurdaspur, Punjab, INDIA. ____________________________________________________________________________________ Abstract: Clustering algorithms are used to classify different objects and their behavior and properties with other objects. These algorithms are mainly used to analyze microarray data and gene comparisons. In this paper we compared some algorithms i.e. hierarchical algorithms, K-means and Fuzzy C-means algorithms according to their performance, size, software and dataset used and their applications. These clustering algorithms are very valuable in recognizing the genes and its sample data. Thus we can easily analyze gene expression data of different genes using these clustering algorithms. Through these comparisons between different algorithms, we compare which algorithm works more efficiently considering different metrics without degrading its performance.
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