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Mining Archived ITS Data for Multidimensional Analysis

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New Approaches for Multidimensional Signal Processing

computer vision systems, multidimensional multimedia systems, neural networks for MD image processing, data-based MD image retrieval and knowledge;

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Quantitative Data Analysis for Language Assessment Volume II

Quantitative Data Analysis for Language Assessment Volume II: Advanced Methods demonstrates advanced quantitative techniques for language;

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Quantitative Data Analysis for Language Assessment Volume II

Quantitative Data Analysis for Language Assessment Volume II: Advanced Methods demonstrates advanced quantitative techniques for language;

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Multidimensional Mining of Massive Text Data

such multidimensional knowledge from massive text data remains a challenging task.This book presents data mining techniques that turn;

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Multidimensional Mining of Massive Text Data

such multidimensional knowledge from massive text data remains a challenging task. This book presents data mining techniques that turn;

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Data Analytics

and data mining; graph data querying and analysis; multidimensional data and data quality; and distributed and multimedia data management.;

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Understanding Biplots

to be a useful and reliable method for the visualization of multidimensional data associated with, for example, principal component analysis;

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Market Research and Modeling: Progress and Prospects

Scaling, Conjoint Analysis, Applications of Conjoint and MDS technique, Data Mining, Cluster Analysis, and Neural Networks.;

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Changes and Bugs

tracking systems, and communications are archived in e-mails and newsgroups. This book presents techniques for mining version archives and bug;

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Microsoft SQL Server 2008 Analysis Services Unleashed

access to data and even more tools for managing and analyzing data across multidimensional objects (databases, dimensions, cubes;

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Data Mining and Big Data

analysis; data mining; text mining; deep learning; high performance computing; knowledge base and its framework; and fuzzy control.;

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Applied Microsoft Business Intelligence

BI architecture, data queries, semantic models, multidimensional modeling, data analysis and visualization, performance monitoring, data;

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Social Big Data Mining

data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language;

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Social Big Data Mining

data, data mining for making a hypothesis, multivariate analysis for verifying the hypothesis, web mining and media mining, natural language;

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Introduction to Computational Health Informatics

trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis Describes computational techniques;

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Introduction to Computational Health Informatics

trees, SVM, and data mining, all of which are techniques used widely used in health-data analysis Describes computational techniques;

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Uncertainty Modelling and Quality Control for Spatial Data

aspects of spatial data quality control. From multidimensional and multi-scale data integration to uncertainties in spatial data mining, this book;

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Uncertainty Modelling and Quality Control for Spatial Data

aspects of spatial data quality control. From multidimensional and multi-scale data integration to uncertainties in spatial data mining, this book;

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Tensor Networks for Dimensionality Reduction and Large-scale Optimization

Modern applications in engineering and data science are increasingly based on multidimensional data of exceedingly high volume, variety;

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R and Data Mining

R and Data Mining introduces researchers, post-graduate students, and analysts to data mining using R, a free software environment for;

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Statistical Data Mining Using SAS Applications

of user-friendly data mining SAS tools. Integrating the statistical and graphical analysis tools available in SAS systems, the book provides;

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Data Mining

Data mining is an important branch of computer science and information technology management that deals with the discovery and analysis;

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Contrast Data Mining

A Fruitful Field for Researching Data Mining Methodology and for Solving Real-Life ProblemsContrast Data Mining: Concepts, Algorithms, and;

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Domain Driven Data Mining

economy,and ub- uitouscomputingandnetworkingacrosseverysectorand business,data andits deep analysis becomes a particularly important issue for;

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Predictive Analytics and Data Mining

and predictions. Data Mining has become an essential tool for any enterprise that collects, stores and processes data as part of its;

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Data Mining Techniques 3rd

cover more advanced topics such as preparing data for analysis and creating the necessary infrastructure for data mining at your company;

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