Multiobjective Genetic Algorithms for Clustering Applications in Data Mining and Bioinformatics /

• Κύριοι συγγραφείς: Maulik, Ujjwal (Συγγραφέας), Bandyopadhyay, Sanghamitra (Συγγραφέας), Mukhopadhyay, Anirban (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.
• Θέματα: Computer science.; Data mining.; Artificial intelligence.; Bioinformatics.; Computational intelligence.; Computer Science.; Artificial Intelligence (incl. Robotics).; Computational Biology/Bioinformatics.; Data Mining and Knowledge Discovery.; Computational Intelligence.

This is the first book primarily dedicated to clustering using multiobjective genetic algorithms with extensive real-life applications in data mining and bioinformatics. The authors first offer detailed introductions to the relevant techniques – genetic algorithms, multiobjective optimization, soft...

Πίνακας περιεχομένων:

• Introduction
• Genetic Algorithms and Multiobjective Optimization
• Data Mining Fundamentals
• Computational Biology and Bioinformatics
• Multiobjective Genetic-Algorithm-Based Fuzzy Clustering
• Combining Pareto-Optimal Clusters Using Supervised Learning
• Two-Stage Fuzzy Clustering
• Clustering Categorical Data in a Multiobjective Framework
• Unsupervised Cancer Classification and Gene Marker Identification
• Multiobjective Biclustering in Microarray Gene Expression Data
• References
• Index.