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Constrained Clustering

Since the initial work on constrained clustering, there have been numerous advances in methods, applications, and our understanding of the;

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Exact Algorithms for Size Constrained Clustering

one in Mathematics and Statistics for Computational Sciences. The series includes selected PhD Theses of the School for a better diffusion;

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Partitional Clustering via Nonsmooth Optimization

implementation, evaluation, and applications. The book gives a comprehensive and detailed description of optimization approaches for solving clustering;

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Partitional Clustering via Nonsmooth Optimization

implementation, evaluation, and applications. The book gives a comprehensive and detailed description of optimization approaches for solving clustering;

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Apache Mahout Clustering Designs

Explore clustering algorithms used with Apache Mahout About This Book * Use Mahout for clustering datasets and gain useful insights;

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Data Clustering in C++

algorithms. This book was written for anyone who wants to implement or improve their data clustering algorithms. Using object-oriented design;

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Data Clustering in C++

algorithms. This book was written for anyone who wants to implement or improve their data clustering algorithms. Using object-oriented design;

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Evolutionary Data Clustering

for data clustering. The book provides literature reviews about single objective and multi-objective evolutionary clustering algorithms;

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Partitional Clustering Algorithms

This book focuses on partitional clustering algorithms, which are commonly used in engineering and c;...

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Complex Scheduling

This book presents models and algorithms for complex scheduling problems. Besides resource-constrained project scheduling problems with;

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Data Clustering and Image Segmentation Through Genetic Algorithms

for IT professionals, computer engineers, researchers, academicians, and upper-level students seeking coverage on how to develop efficient;

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Lecture Notes In Data Mining

The continual explosion of information technology and the need for better data collection and management methods has made data mining an;

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Bayesian Missing Data Problems

techniques, and optimization methods. It then gives exact posterior solutions for problems, such as nonresponses in surveys and cross-over trials;

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Bayesian Missing Data Problems

techniques, and optimization methods. It then gives exact posterior solutions for problems, such as nonresponses in surveys and cross-over trials;

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Fuzzy Sets & their Application to Clustering & Training

Clustering and Training offers a comprehensive introduction to fuzzy set theory, focusing on the concepts and results needed for training and;

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Recent Advances in Hybrid Metaheuristics for Data Clustering

intelligence techniques Recent Advances in Hybrid Metaheuristics for Data Clustering offers a guide to the fundamentals of various metaheuristics;

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Metaheuristic Clustering Algorithm

methods for clustering complex data sets and improve performance of some algorithms that illustrated in the literature. Experimental results are;

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Clustering in Bioinformatics and Drug Discovery

drug discovery. Setting the stage for subsequent material, the first three chapters of the book introduce statistical learning theory;

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Clustering in Bioinformatics and Drug Discovery

drug discovery. Setting the stage for subsequent material, the first three chapters of the book introduce statistical learning theory;

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Parameterized and Exact Computation

limited to new techniques for the design and analysis of parameterized and exact algorithms, fixed-parameter tractability results, parameterized;

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Secure Clustering in Multi-Modal Wireless Sensor Networks

In this work we propose two security frameworks merging Elliptic Curve Cryptography (ECC) with symme;...

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Parameterized and Exact Computation

including but are not limited to new techniques for the design and analysis of parameterized and exact algorithms, fixed-parameter tractability;

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Computational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis;

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Pathway Modeling & Algorithm Research

approximation schemes for functional optimisation.;

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Unsupervised Machine Learning for Clustering in Political and Social Research

In the age of data-driven problem-solving, applying sophisticated computational tools for explaining substantive phenomena is a valuable;

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Data Mining Algorithms

Data Mining Algorithms is a practical, technically-oriented guide to data mining algorithms that covers the most important algorithms for;

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Stochastic Linear Programming Algorithms

A computationally oriented comparison of solution algorithms for two stage and jointly chance constrained stochastic linear programming;

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