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Clustering Methodology for Symbolic Data

Symbolic data analysis is a relatively new field that provides a range of methods for analyzing complex datasets. Standard statistical;

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Data Analysis and Rationality in a Complex World

developments and practical applications related to classification and clustering, data gathering, exploratory and multivariate data analysis;

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Medical Biostatistics for Complex Diseases

high-throughput data derived from studies of complex diseases. Such diseases include cancer and cardiovascular disease, and constitute the;

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Predictive Analytics and Data Optimization

Data analysis models and techniques have rapidly evolved in last few decades to unfold patterns and information from large and complex;

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Practical Parallel Computing

applications, data transfer and storage cost minimisation, two-stroke engine applications, large air pollution models, parallel global aircraft;

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Large Scale Structure And Dynamics Of Complex Networks

the various problems in data analysis visualization and modeling of complex networks.;

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Complex Surveys

, two-phase designs, and fitting of regression models to survey data Complex Surveys is the first book to describe the use of R in survey;

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Analysis of Large and Complex Data

component. The topics addressed are from the following fields: Statistics and Data Analysis; Machine Learning and Knowledge Discovery; Data Analysis;

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Interactive Visual Data Analysis

modern interaction technology can facilitate the visual data analysis in many ways. Addressing today's large and complex data, the book covers;

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Interactive Visual Data Analysis

modern interaction technology can facilitate the visual data analysis in many ways. Addressing today's large and complex data, the book covers;

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Statistical Analysis of Gene Expression Microarray Data

Although less than a decade old, the field of microarray data analysis is now thriving and growing at a remarkable pace. Biologists;

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Big Data of Complex Networks

Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural;

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Big Data of Complex Networks

Big Data of Complex Networks presents and explains the methods from the study of big data that can be used in analysing massive structural;

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Understanding Complex Datasets

applications, this resource helps you model large, complex datasets and investigate connections between standard data mining techniques and matrix;

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Predictive Analysis with SAP: The Comprehensive Guide

examples, customer case studies, and explanations of the business benefits, this book helps you navigate the complex predictive analysis process;

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Practical Methods For Design And Analysis Of Complex Surveys

in descriptive surveys, including design effect statistic and use of auxiliary data. Includes detailed coverage of complex survey analysis, including;

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Data Analysis in the Cloud

Data Analysis in the Cloud introduces and discusses models, methods, techniques, and systems to analyze the large number of digital;

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Large-Scale Data Analytics

challenges for the efficient analysis of the data under numerous constraints, including consistent data integration, data homogenization and scaling;

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Learning Representation for Multi-View Data Analysis

classification, zero-shot learning, and domain adaption. More practical challenges in multi-view data analysis are discussed including incomplete;

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Symbolic Data Analysis and the SODAS Software

Symbolic data analysis is a relatively new field that provides a range of methods for analyzing complex datasets. Standard statistical;

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Foundations of Data Science

-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear;

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Methodological Developments in Data Linkage

the 1950-60s, with some updates. Linkage and analysis of data across sources remains problematic due to lack of discriminatory and accurate;

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Deep Learning for Data Analytics

analysis. Deep learning transforms data through a cascade of layers, helping systems analyze and process complex data sets. Deep learning;

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Fundamentals of Big Data Network Analysis for Research and Industry

Fundamentals of Big Data Network Analysis for Research and Industry Hyunjoung Lee, Institute of Green Technology, Yonsei University;

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Multi-Objective Optimization utilizing Cluster Analysis applied to Dimensional Transposed Problems

With respect to the importance of multi-objective optimization in the context of the today's information processing and analysis, as well;

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Data Science and Data Analytics

complex behaviors, trends, and inferences) from data. Moreover, Big Data analyticsdata analytics are the analysis mechanisms used in data science;

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Research in the College Context

research, policy analysis, document analysis and historical methods, secondary data analysis, and use of large national data sets. This revised;

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