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Pro Linux High Availability Clustering

solution based on that scattered information, which is often oriented towards specific tasks only. Pro Linux High Availability Clustering explains;

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Clustering

explore: proximity measures; hierarchical clustering; partition clustering; neural network-based clustering; kernel-based clustering; sequential;

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Partitional Clustering Algorithms

goal of this volume is to summarize the state-of-the-art in partitional clustering. The book includes such topics as center-based clustering;

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Partitional Clustering via Nonsmooth Optimization

This book describes optimization models of clustering problems and clustering algorithms based on optimization techniques, including their;

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Partitional Clustering via Nonsmooth Optimization

This book describes optimization models of clustering problems and clustering algorithms based on optimization techniques, including their;

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Data Clustering

used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic;

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Oracle Solaris and Veritas Cluster : An Easy-build Guide

the architecture design and technical implementation for building Solaris Oracle- or Veritas-based clustered environments. This book provides;

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A Graph Theoretic Approach to Heterogeneous Data Clustering

-clustering. First, we propose a semantic-based hierarchical image clustering framework based on multi-user feedback. By treating each user as an;

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Temporal Data Mining via Unsupervised Ensemble Learning

blend of theory and practice. Furthermore, the book includes illustrations of the proposed approaches based on data and simulation;

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Model-Based Clustering and Classification for Data Science

approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering;

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Projection Based Clustering through Self Organization and Swarm Intelligence

verified by the 3D landscape at a glance. DBS is the first swarm-based technique that shows emergent properties while exploiting concepts of swarm;

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Apache Mahout Clustering Designs

clusters. This book will discuss about cluster improvement and visualization using Mahout APIs and also explore model-based clustering and topic;

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Time Series Clustering and Classification

developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification;

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Time Series Clustering and Classification

relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based;

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Secure Clustering in Multi-Modal Wireless Sensor Networks

based clustering technique that takes node's residual energy, density and number of features sensed in Multi-Modal WSNs. We propose a novel data;

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Projection-Based Clustering Through Self-Organization and Swarm Intelligence

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Knowledge-Based Clustering

A comprehensive coverage of emerging and current technology dealing with heterogeneous sources of in;...

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Constrained Clustering

Since the initial work on constrained clustering, there have been numerous advances in methods, appl;...

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Combining DBSCAN and Grid Based Clustering For Performance Analysis

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Improved Scheduling Algorithm Using Dynamic Tree Construction for Wireless Sensor Networks

algorithm based on Distance and Residual Energy for Wireless Sensor Networks (DECSA) which describes scheduling based on distance and energy, and;

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Adaptive Resonance Theory in Social Media Data Clustering

unsupervised knowledge discovery and data mining A class of neural inspired algorithms, based on adaptive resonance theory (ART), tackling challenges;

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Modern Algorithms of Cluster Analysis

. The book explains feature-based, graph-based and spectral clustering methods and discusses their formal similarities and differences;

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Integrative Cluster Analysis in Bioinformatics

Clustering techniques are increasingly being put to use in the analysis of high-throughput biologica;...

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A Clustering-Based Approach for Discovering Places in Trajectories

This work is a clustering point of view about how deduce interesting places considering the points a;...

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Social Clustering

-based family, community, and regional and national prosperity. Aspiration for common objective; consensus on the most important priorities;

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Data Clustering

clustering algorithms in groups according to some specific baseline methodologies such as hierarchical, center-based, and search-based methods. As a;

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Customer Payment Trend Analysis based on Clustering for Predicting the Financial Risk of Business Organizations

Customer Payment Trend Analysis Based On is een boek van Jeeva Jose;

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