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Application of Data Mining Techniques in the Analysis of Indoor Hygrothermal Con

The main benefit of the book is that it explores available methodologies for both conducting in-situ measurements and adequately exploring;

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Data Mining for Biomarker Discovery

informatics. This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new;

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Data Mining for Bioinformatics

, overview of the application domains of data mining for bioinformatics to help readers from both biology and computer science backgrounds gain an;

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Data Mining for Bioinformatics

, overview of the application domains of data mining for bioinformatics to help readers from both biology and computer science backgrounds gain an;

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Hygrothermal Behaviour and Building Pathologies

techniques, and highlights the latest developments in building physics, hygrothermal behaviour, durability and numerical models applied to building;

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Python Geospatial Analysis Cookbook

formats to prepare it for your application or spatial analysis * Use the power of PostGIS with Python to take advantage of the powerful analysis;

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Practical Graph Mining with R

graphs. Hands-On Application of Graph Data Mining Each chapter in the book focuses on a graph mining task, such as link analysis, cluster;

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Data Mining Techniques In Crm

This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business;

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Applications and Developments in Semantic Process Mining

classical process mining techniques to semantical preparation of the extracted models for further analysis and querying at a more abstract level;

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Applications and Developments in Semantic Process Mining

classical process mining techniques to semantical preparation of the extracted models for further analysis and querying at a more abstract level;

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Data Mining and Predictive Analysis

anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive;

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Computationally Intensive Statistics for Intelligent IoT

of experiments, Bayesian analysis, survival analysis and data mining in computational statistics.;

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Rapidminer

and Business Analytics Applications provides an in-depth introduction to the application of data mining and business analytics techniques and;

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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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Data Mining Techniques 3rd

Techniques in the late 1990s, data mining was just starting to move out of the lab and into the office and has since grown to become an indispensable;

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Real-World Data Mining

, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration. Throughout;

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Handbook of Statistical Analysis and Data Mining Applications

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that;

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New Frontiers in Applied Data Mining

application of data mining techniques to new frontiers. Thus the title of the proceedings: New Frontiers in Application of Data Mining. For the 2008;

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Mathematical Analysis For Machine Learning And Data Mining

This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The;

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Data Fusion and Data Mining for Power System Monitoring

fusion techniques are reviewed, with emphasis on the analysis and visualization of massive distributed data sets. Challenges involved;

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Data Fusion and Data Mining for Power System Monitoring

fusion techniques are reviewed, with emphasis on the analysis and visualization of massive distributed data sets. Challenges involved;

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Sentic Computing

language data and the concept-level opinions conveyed by these. In particular, the ensemble application of graph mining and multi-dimensionality;

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Data Mining and Knowledge Discovery for Geoscientists

Currently there are major challenges in data mining applications in the geosciences. This is due primarily to the fact that there is a;

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Privacy-Aware Knowledge Discovery

-of-the-art privacy-preserving data mining techniques for application domains, such as medicine and social networks, that face the increasing;

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Privacy-Aware Knowledge Discovery

-of-the-art privacy-preserving data mining techniques for application domains, such as medicine and social networks, that face the increasing;

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Contrast Data Mining

Applications collects recent results from this specialized area of data mining that have previously been scattered in the literature, making them more;

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